19
Research Article Complex Effects of Drum Hub Forms and Structural Parameters on Coal Loading Performance Kuidong Gao , 1,2 Xiaodi Zhang , 1 Liqing Sun, 1 Qingliang Zeng , 1,2 andKaoJiang 1 1 College of Mechanical & Electrical Engineering, Shandong University of Science & Technology, Qingdao 266590, China 2 Shandong Province Key Laboratory of Mine Mechanical Engineering, Shandong University of Science and Technology, Qingdao 266590, China Correspondence should be addressed to Kuidong Gao; [email protected] Received 10 January 2020; Revised 15 May 2020; Accepted 21 May 2020; Published 10 June 2020 Academic Editor: Dan Selis ¸teanu Copyright © 2020 Kuidong Gao et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e extremely poor loading performance of a thin coal shearer drum affects the mining efficiency in thin seam mining seriously on account of the restriction by the complicated mining environment and seam thickness. e coal loading performance of the drum is influenced by several complex factors, such as motion parameters and structural parameters, including the structure and form of the hub. e form of the drum hub is cylindrical in general, and in order to study the influence of the hub form on the coal loading rate of the drum, seven drums with different hub forms and structures were designed. e influence of the complexity of hub structures on the coal loading performance was studied by discrete element method (DEM) simulation in this paper. e change curves with the research object of different drums, such as coal loading rate, velocity field distribution, and contact force between fallen coal particles, were obtained. e results showed that the conical hub drum can improve the coal loading performance than the cylindrical hub drum, and the curve-shaped hub drum had a more obvious promotion on the coal loading performance. e coal loading rate increased first and then decreased with the increase of hub cone angle. Compared with the conical hub drum, the curve-shaped hub drum can not only improve the coal loading rate, but also has a larger space containing coal. is study has proposed a drum with a new form hub which could increase the coal loading rate, and the methods and conclusions provide the guidance for drum hub design. 1.Introduction e shearer is the important device in longwall mining, whose performance affects the mining capacity and effi- ciency directly. As a main component of the shearer, the drum is mainly used for coal cutting and loading, whose performances are the key factors that influence the shearer performance. e cutting action of the drum has been studied by the scholars’ abundant research studies [1, 2]; Yang et al. [3] studied the wear in conical picks in rotation- drilling cutting progress by experimental and theoretical methods. Zhao et al. [4] used ANSYS/LS-DYNA software to study the dynamic transmission law of the spiral drum cutting coal rock and obtained the stress distribution of the drum in the cutting process. Liu et al. [5] proposed a new three-drum shearer and studied the cutting performance of the pick in deep coal conditions. Huang et al. [6] used the finite element method to simulate rock cutting process under confining pressure and obtained the influence of confining pressure on the cutting force. However, the re- search studies about loading action of the drum are still insufficient, and many research studies were conducted in the last century. e coal conveying performance of the drum is influenced by several factors which include vane, hub, wear-resistant plate, picks, and pick holder, and the influences are in complexity. As the complex mining con- ditions and environment are with smaller mining heights in the thin coal seam, the diameter of the drum and the depth of the vane are small, resulting in the complex coal loading procedure and poor loading performance which caused the lower mining efficiency and the increment of the labor input. erefore, the study about the coal loading performance of Hindawi Complexity Volume 2020, Article ID 7036087, 19 pages https://doi.org/10.1155/2020/7036087

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Research ArticleComplex Effects of Drum Hub Forms and StructuralParameters on Coal Loading Performance

Kuidong Gao 12 Xiaodi Zhang 1 Liqing Sun1 Qingliang Zeng 12 and Kao Jiang 1

1College of Mechanical amp Electrical Engineering Shandong University of Science amp Technology Qingdao 266590 China2Shandong Province Key Laboratory of Mine Mechanical Engineering Shandong University of Science and TechnologyQingdao 266590 China

Correspondence should be addressed to Kuidong Gao gaokuidong22163com

Received 10 January 2020 Revised 15 May 2020 Accepted 21 May 2020 Published 10 June 2020

Academic Editor Dan Selisteanu

Copyright copy 2020 Kuidong Gao et al +is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

+e extremely poor loading performance of a thin coal shearer drum affects the mining efficiency in thin seammining seriously onaccount of the restriction by the complicated mining environment and seam thickness+e coal loading performance of the drumis influenced by several complex factors such as motion parameters and structural parameters including the structure and form ofthe hub+e form of the drum hub is cylindrical in general and in order to study the influence of the hub form on the coal loadingrate of the drum seven drums with different hub forms and structures were designed +e influence of the complexity of hubstructures on the coal loading performance was studied by discrete element method (DEM) simulation in this paper +e changecurves with the research object of different drums such as coal loading rate velocity field distribution and contact force betweenfallen coal particles were obtained+e results showed that the conical hub drum can improve the coal loading performance thanthe cylindrical hub drum and the curve-shaped hub drum had a more obvious promotion on the coal loading performance +ecoal loading rate increased first and then decreased with the increase of hub cone angle Compared with the conical hub drum thecurve-shaped hub drum can not only improve the coal loading rate but also has a larger space containing coal +is study hasproposed a drum with a new form hub which could increase the coal loading rate and the methods and conclusions provide theguidance for drum hub design

1 Introduction

+e shearer is the important device in longwall miningwhose performance affects the mining capacity and effi-ciency directly As a main component of the shearer thedrum is mainly used for coal cutting and loading whoseperformances are the key factors that influence the shearerperformance +e cutting action of the drum has beenstudied by the scholarsrsquo abundant research studies [1 2]Yang et al [3] studied the wear in conical picks in rotation-drilling cutting progress by experimental and theoreticalmethods Zhao et al [4] used ANSYSLS-DYNA software tostudy the dynamic transmission law of the spiral drumcutting coal rock and obtained the stress distribution of thedrum in the cutting process Liu et al [5] proposed a newthree-drum shearer and studied the cutting performance of

the pick in deep coal conditions Huang et al [6] used thefinite element method to simulate rock cutting processunder confining pressure and obtained the influence ofconfining pressure on the cutting force However the re-search studies about loading action of the drum are stillinsufficient and many research studies were conducted inthe last century +e coal conveying performance of thedrum is influenced by several factors which include vanehub wear-resistant plate picks and pick holder and theinfluences are in complexity As the complex mining con-ditions and environment are with smaller mining heights inthe thin coal seam the diameter of the drum and the depth ofthe vane are small resulting in the complex coal loadingprocedure and poor loading performance which caused thelower mining efficiency and the increment of the labor input+erefore the study about the coal loading performance of

HindawiComplexityVolume 2020 Article ID 7036087 19 pageshttpsdoiorg10115520207036087

the drum is extremely important and necessary +roughsummarizing the research results of previous scholars on theshearer drum in the medium and thick coal seam the in-fluence of the drum structure and motion parameters on thecoal loading performance of the drum was obtained byBrooker [7] Ludlow and Jankowski [8] concluded that thewrap angle of vanes should be less than 360deg and the morevane number and material speed would reduce the drumloading rate +e factors which include the number of vaneswrap angle of vanes drum rotational speed and haulingspeed that affected the drum loading performance werepointed out by Peng [9] andHurt andMcstravick [10] Basedon the previous research studies the loading performance ofa new style drum called ldquoGloboid drumrdquo was investigated byAyhan and Eyyuboglu [11] and they proved the higherloading performance of this drum Liuet al [12] studied theeffects of factors such as the vane helix angle drum rota-tional speed and hauling speed on the coal loading rate ofthe drum and found the matching parameter with the bestcoal loading performance by using the coal-rock cutting test-bed In addition to the above research studies Gao et al [13]also studied the influence of working face conditions andstructures of the ranging arm of the shearer on the drum coalloading rate by DEM simulation Bołoz [14] designed a typeof longwall shearer which was applicable to mining thinhard coal seams and this shearer operation technology andpossible daily output achievement were introduced in hisstudy in detail In 2015 Wydro [15] researched the influ-ences of filling rate and coal plate on the transport rate of thebulk coal with the help of a self-developed drum test benchfor coal transport In 2016 the coal loading process of ashearer was simulated by Gospodarczyk [16] using PFC3Dand the drum transport effect and coal particle movementsunder circumstances of cutting top coal cutting bottom coaland with and without the coal plate were studied

In order to study the complex transportation process ofbulk materials better Cundall and Strack [17 18] put for-ward the DEM for the first time With the development ofnumerical simulation technology the DEM has been widelyused in the fields of bulk material transportation materialscreening rock cutting rock crushing pharmaceutical en-gineering and fluidized bed [19ndash22] Meanwhile manyscholars have also completed the design and performanceanalysis of complex mechanical structures such as feeder[23] chain conveyor [24] and belt conveyor [25] Potyondyand Cundall [26] proposed that the DEM can simulate thebulk properties of the real coal rock after crushing and thecrushed coal rock had the properties of the granular ma-terial so the DEM can be applied to the analysis of the coalloading performance of the drum Dai et al [27] performedthe uniaxial and triaxial numerical simulations of seafloormassive sulfides by leveraging the PFC3D code and pre-dicted the maximum force on the cutting pick Li et al [28]studied the drum cutting properties through DEM simu-lations and concluded that the DEM is an easier faster andreasonable method in the prediction of drum cutting loadand design of the shearer drum Furthermore Gao [29]combined the experimental research and the DEM simu-lation to study the influence of the helix angle of the blade on

the coal loading performance and proved the accuracy andfeasibility of the DEM in the simulation of coal conveyingprocess of the drum

Several scholars have conducted considerable researchstudies with experimental verification and DEM simula-tion on factors affecting the coal loading performance ofthe drum including motion parameters (rotational speedand hauling speed) and structure parameters (the numberand helix angle of blades and web depth) of the drum butthe research about the influence of the structure of the hubon the coal loading performance was not reportedStudying the coal conveying performance of the drumwith the experimental method was high cost and themacroscopic appearance could be observed merely whilethe essence of influences in complexity at a microlevelcould not be revealed +erefore this paper studied thecoal loading rate the three-direction velocity of coalparticles the number of particles in different web depthsand the contact force of particles under different struc-tures of the drum hub by the DEM In the results of thispaper the influence of the hub form and structures andthe rotational speed of the drum on the coal loading rateand the coal particle conveying process was obtained andthe character of these complex influences was discussedand analyzed +is study provides a reference and guid-ance for the design of the drum hub and the workingparameter selection of the shearer in the complex workingenvironment such as thin coal seams

2 Methodology

+e DEM has been applied in different fields by manyscholars worldwide to solve many complex engineeringproblems According to the research content of this paperthe coal face is a cohesive body with continuous propertybefore crushing and then the broken coal can be regarded asa loose material with discrete property after crushing +ebonding model proposed by Potyondy and Cundall [26] cansimulate the continuity of the coal before breaking so thebonding model is selected as the model of building the coalface in the DEM In order to describe the contact force anddisplacement between particles and the relative movementof particles the linear contact model and the sliding modelare selected in the DEM

21 Linear Contact Model +e relationship between parti-cles of normal contact force shear contact force and dis-placement in the linear contact model can be expressed asfollows

Fni KnUnni

ΔFsi minusKsΔUs

i 1113896 (1)

where Fni is the normal contact force Fs

i is the shear contactforce Un is the tangential displacement increment Us

i is theshear component of the contact displacement-incrementvector Kn is the normal contact stiffness Ks is the shearcontact stiffness ni is the unit normal vector of particles andi is the number of particles

2 Complexity

+e normal contact stiffness can be expressed as follows

Kn

k[A]

n k[B]n

k[A]n + k

[B]n

(2)

where k[A]n and k[B]

n are the normal stiffness of two contactparticles

+e shear contact stiffness can be expressed as follows

Ks

k[A]

s k[B]s

k[A]s + k

[B]s

(3)

where k[A]s and k[B]

s are the normal stiffness of two contactparticles

22 SlipModel +e slip is enforced by verifying whether themaximum static friction force is exceeded by the shearingforce +e maximum static friction force is calculated usingthe minimum friction coefficient μ and this friction forcecan be expressed as follows

Fsmax μ F

ni

11138681113868111386811138681113868111386811138681113868 (4)

+e slip will occur between the two contact particleswhen the shear contact force Fs

i meets |Fsi |gtFs

max in equation(4)

23 Bonding Model +e bonding model is mainly used todetermine the contact between two particles before the coalface is broken Since this paper mainly studied the cutoff coalparticle conveying performance of the drum the normal andthe tangential bonding strength between the particles onlyneed to ensure that the coal face can maintain a staticstructure during the cutting process When the force exertedon the particles in the normal and tangential directionexceeds the tensile or tangential bond strength the bondbetween particles breaks and the particles are cut off +econstitutive behavior for contact occurring at a point isindicated in Figure 1

+e fatigue failure criterion of two bonding models canbe expressed as follows

Fcn geRn

Fcs geRs

1113896 (5)

where Rn and Rs are the normal and the tangential bondingstrength of the particles respectively

3 Simulation Model Establishment

In an ideal coal mining process the coal cutoff from the coalface could be loaded by the drum onto the middle chute ofthe conveyor and transported out of the working faceHowever some of the fallen coal were thrown to the goaf andbecame the floating coal In addition some other fallen coalpiled up in the area between the coal face and the chainconveyor due to the insufficient axial velocity and led to anegative impact on the move of the conveyor towards thecoal face Based on the above problems the effect of thedrum on particle ejection speed and axial velocity has animportant impact on the coal loading performance In

addition to the influence of the motion parameters and thestructure parameters of the vane the structure parameters ofthe hub also play an important role in affecting the motionbehavior of particles +erefore four drums with the conicalhub were designed on the basis of the cylinder hub drum asshown in Figure 2 (I) (II) (III) (IV) and (V) whereΨ is thecone angle of the hub but the conical hub leads to a lowerdrum space capacity to a certain extent so three drums withthe curve-shaped hub were designed as shown in Figure 2(VI) (VII) and (VIII) where Ki is the average curvature ofthe hub+e curve-shaped hub drums not only increased theaxial velocity of coal particles but also provided the biggerdrum space capacity and the parameters of the drum hubare shown in Table 1 As one of the motion parameters of thedrum the rotational speed has important and compleximpacts on the loading performance of the drum+ereforethis paper studied the coal loading performance of the drumcombined with the effects of structures of the drum hub andthe rotational speed and the optimal matching relationshipbetween the rotational speed and hub structures wasobtained

+e equipment on the underground coal miningworking face and the numerical simulation model are il-lustrated in Figure 3(a) +e equipment of the coal miningworking face is mainly composed of a shearer a hydraulicsupport and a chain conveyor for coal cutting and loadingsupporting the roof and transportation respectively As themain research object the drum model was established insimulation Additionally it has been proved that the rangingarm of the shearer and the relative position relationshipbetween the chain conveyor and the drum have a significanteffect on the coal loading rate [13 30] so the ranging armand the chain conveyor model were also established insimulation In order to reduce simulation time and simplifythe model the hydraulic support which would not affect thesimulation result was not established In the working processof the drum its rotation direction includes from the rooftowards the floor and from the floor towards the roofcorresponding to two coal loadingmethods of drum pushingand drum ejection as shown in Figure 3(b) Figure 4 showsthe comparison of the coal loading rate of different drumswith drum pushing and ejection and the results of the coalloading rate of drum (I) with drum pushing and ejectionunder different rotational speeds It can be seen that the coalloading rate with the drum ejection method was better thanthat of the drum pushing method obviously In the processof mining thin coal seam the coal cutting and loadingmainly depend on the front drum+erefore this paper onlyfocused on the coal loading performance with the drumejection method

+e particle and material parameters in the simulationare shown in Table 2 +e parameters of the drum structuresweb depth diameter of the loading vane helix angle and thediameter of the hub were 650mm 800mm 23deg and400mm respectively In order to study the loaded coalparticles with different web depths the coal face particleswere dyed according to web depth in which the width ofgreen red blue and yellow particles was 150mm and thewidth of orange particles was 50mm In the simulation

Complexity 3

process the coal falling area was divided into three parts+egoaf was area I the area between the middle chute of thechain conveyor and the coal face was area II and the middlechute of the chain conveyor was area III which is the sta-tistical area of loaded particles +e coal loading rate was theratio of the loaded coal particle mass in area III and the total

fallen coal particle mass as shown in Figure 5 Due to theinteraction between the drum and the coal particles in thecoal loading process the movement of the coal particlesshowed randomness and complexity In order to reveal thecoal loading mechanism and the drum-particle interactionmechanism of drums with different hubs the number and

Ftangential

Fnormalks

kn

PiR

Dashpot

Pj R

Dashpot

μ

(a)

Bond breaks

Bond breaks

Fcn

FcsTensionkbnkbs

l l

Shear

Un(Us)Compression

(b)

Figure 1 (a) +e particle contact model in the DEM (b) constitutive behavior in the contact bonding model

ψ = 90deg ψ = 95deg ψ = 100deg ψ = 105deg

ψ = 110degψ = 110deg

ψ = 105degψ = 100deg

ψ = 100degψ = 100deg

ψ = 90degψ = 90degψ = 95deg

ψ = 95deg

K1 K2 K3K1

K2 K3K1 K2 K3

Figure 2 +e drums with different forms and structures of the hub

Table 1 +e structure parameters of the drum hub

Drum I II III IV V VI VII VIII

Ψ (deg)Ki 90 95 100 105 110K1 1638eminus 1K2 1001eminus 1

K3 0

K1 1224eminus 1K2 7984eminus 2K3 2735eminus 2

K1 1017eminus 1K2 5401eminus 2

K3 0

4 Complexity

velocity of particles at different positions inside the drumwere counted Hence based on each cut line of the pick onthe vane the envelop zone of the loading vane was used asthe statistical zone and the width of the hub was dividedinto five equal zones as shown in Figure 6 so as to ensurethat each statistical zone had the same amount of particlescut from the coal face in unit time Furthermore the right

half of the drum and the coal face formed a closed areawhile the left half was an open area and the vanes mainlyinteract with the particles in the right half of the drum Inorder to study the contact force and the conveying per-formance of particles inside the drum the right half of thedrum was divided into two equal statistical areas as shownin Figure 6

ShearerCoal face

Drum

Ranging arm

Hydraulic supportChain conveyor

Roof

DrumRanging arm

Chain conveyor

Coal face

(a)

Coal loading with drum ejection

Direction ofdrum rotation

from floortowards roof

Hauling direction

Hauling direction

Coal loading with drum pushing

Direction ofdrum rotation

from rooftowards floor

(b)

Figure 3 (a) Shearer in operation (b) the coal loading process of the drum in simulation

Drum I with pushing

Drum I with ejection

Coal loading with drumpushingCoal loading with drumejection

II III IV V VI VII VIIIIDrum

35

40

45

50

55

60

65

Coa

l loa

ding

rate

()

40 60 80 100Rotational speed (rpm)

Figure 4 +e comparison of different coal loading methods

Table 2 +e parameters of the particle in the simulation

Density (kgm3) Poissonrsquos ratio Youngrsquos modulus (GPa)Coal 1400 028 425Steel 7800 030 206

Coefficient of restitution Coefficient of static friction Coefficient of rolling frictionCoal-coal 050 080 010Coal-steel 050 060 005

Complexity 5

4 Analysis of the Simulation Resultsand Discussion

41 e Influence of the Rotational Speed and the HubStructure on Coal Particle Velocities in ree DirectionsIn the simulation process the hauling speed of the drum wasset to 4mmin and the rotational speed was 40 rpm 60 rpm80 rpm and 100 rpm respectively +e velocities of particlesinfluenced by the combination of drum hub structures androtational speed were studied Figure 7 demonstrates thevariation curves of the coal loading rate of eight drums withrotational speed For different matching of the hub struc-tures and drum rotational speed the relationship betweenthe particle velocities and the coal loading rate has beenshown in Table 3 and Figure 8

As indicated in Figure 7 with the increase of the value ofΨ the rotational speed required for the drum to obtain thebest coal loading performance decreases In the case of the

same rotational speed the particle velocity under differentdrums in X and Z directions was not different signifi-cantly while that in the Y direction namely the axialdirection was significantly different as shown in Figure 8and Table 3 +e axial velocity of particles increased withthe increase of the value of Ψ and the lower the rotationalspeed the more obvious the difference When the rota-tional speed increased from 40 rpm to 100 rpm the ve-locity difference in the Y direction between drums (V) and(I) decreased from four times higher to two times +ereason for that was when the rotational speed was smallthe packing density of particles inside the drum was largeand the hub had an obvious impact on the particles Withthe increase of the rotational speed the packing density ofparticles inside the drum decreases which leads to thedecrease of contact between the hub and particles and thevanes gradually played a leading role resulting in thereduction of the velocity difference In the case of the same

Z

X

Y

Area I

Area II

Area III

Area I goafArea II the areabetween coal face andchain conveyor

Area III the effectiveloading area in chute ofchain conveyor

Figure 5 Statistical area division of coal loading

A B C DE

Z

Y1

2

X

View A

n

1

2

Z

X

Hauling direction

View A

(a)

1

2

3

4

5

1

Vane

A

B

C

D

E

2Pick

A-B

B-C

C-D

D-E

Expanded viewπ2 ndashπ2

(b)

Figure 6 +e statistical zone of the drum with different web depths (a) View A (b) Expanded view

6 Complexity

drum the particle velocity in directions Y and Z increasedwith the increase of the rotational speed while the velocityin the X direction decreased +is is because with theincrease of the rotational speed the action of the vaneswas more obvious and the number and amplitude of thethrown particles increased correspondingly which led to

the increase of the particle velocity in Y and Z directions toan extent Due to the influence of the vanes more particleswere thrown from the right half of the drum to the lefthalf and the movement direction was reversed in the Xdirection resulting in a decrease in the velocity in the Xdirection to some extent

60 80 10040Rotational speed (rpm)

45

50

55

60

65

Coa

l loa

ding

rate

()

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Figure 7 +e coal loading rate curve of eight drums at different rotational speeds

Table 3 +e statistical analysis of particle velocities in three directions and coal loading rate

n (rpm) Drum X direction (ms) Y direction (ms) Z direction (ms) Loading rate ()

40

I 0185 0126 0198 4819II 0243 0209 0217 5275III 0239 0332 0230 5646IV 0219 0371 0244 5590V 0241 0459 0238 5153VI 0288 0464 0266 5667VII 0265 0368 0333 6277VIII 0245 0238 0229 5711

60

I 0276 0200 0211 4999II 0279 0286 0262 5591III 0281 0391 0250 6033IV 0267 0469 0139 5477V 0261 0538 0254 5063VI 0337 0554 0290 5870VII 0333 0462 0317 5948VIII 0261 0319 0234 5877

80

I 0437 0308 0245 5068II 0402 0393 0237 5174III 0461 0511 0283 5424IV 0424 0572 0221 5195V 0429 0680 0211 4844VI 0544 0673 0230 5788VII 0547 0573 0284 5724VIII 0483 0380 0219 5654

100

I 0531 0344 0144 4587II 0546 0430 0190 4825III 0573 0554 0133 5156IV 0577 0621 0138 4957V 0673 0746 0143 4800VI 0691 0722 0128 5375VII 0596 0591 0162 5440VIII 0487 0427 0148 5374

Complexity 7

+e coal loading performance of the drum depends onthe axial velocity of particles to a large extent +rough theanalysis of Table 3 and Figure 8 the axial velocity of particlesand the coal loading rate of the drum increase with theincrease in the value of Ψ but when Ψgt100deg with the in-crease in the value of Ψ the axial velocity of particles stillincreases while the coal loading rate decreases +e reasonfor that is the average diameter of the hub was too large dueto the excessive cone angle and the particles in the drumwere compressed by the hub and fell into area II in the formof extrusion Additionally the axial velocity of particles indrums (VI) (VII) and (VIII) was close to that of drums (V)(IV) and (II) respectively However the diameter of thecurve-shaped hub is smaller than that of the conical hub so

the squeezing effect of the particles by the hub was smallerwhich led to a higher coal loading rate

42 e Influence of the Drum Space Capacity on the CoalConveying Performance +e drum space capacity dependson the diameter of the vane and the hub +e cone angle ofthe hub has a negative impact on the drum space capacityespecially in the case of the lower rotational speed and thecoal cutting rate of the drum is bigger than the conveyingflow rate which is prone to clogging +e theoretical con-veying flow of the drum depends on the axial velocity ofparticles and the swept area by vanes which is expressed byequation (6) +e cutting rate of the drum is determined by

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

00

01

02

03

04

05

06M

ean

velo

city

of p

artic

les (

ms

)

48

51

54

57

60

63

Coa

l loa

ding

rate

()

IIIII IV V VII VIIIVIIDrum

(a)

00

01

02

03

04

05

06

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

48

51

54

57

60

Coa

l loa

ding

rate

()

(b)

48

51

54

57

60

Coa

l loa

ding

rate

()

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

(c)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08M

ean

velo

city

of p

artic

les (

ms

)

45

48

51

54

57

Coa

l loa

ding

rate

()

(d)

Figure 8+e relationship between particle velocity in three directions and loading rate at different rotational speeds (a) 40 rpm (b) 60 rpm(c) 80 rpm and (d) 100 rpm

8 Complexity

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 2: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

the drum is extremely important and necessary +roughsummarizing the research results of previous scholars on theshearer drum in the medium and thick coal seam the in-fluence of the drum structure and motion parameters on thecoal loading performance of the drum was obtained byBrooker [7] Ludlow and Jankowski [8] concluded that thewrap angle of vanes should be less than 360deg and the morevane number and material speed would reduce the drumloading rate +e factors which include the number of vaneswrap angle of vanes drum rotational speed and haulingspeed that affected the drum loading performance werepointed out by Peng [9] andHurt andMcstravick [10] Basedon the previous research studies the loading performance ofa new style drum called ldquoGloboid drumrdquo was investigated byAyhan and Eyyuboglu [11] and they proved the higherloading performance of this drum Liuet al [12] studied theeffects of factors such as the vane helix angle drum rota-tional speed and hauling speed on the coal loading rate ofthe drum and found the matching parameter with the bestcoal loading performance by using the coal-rock cutting test-bed In addition to the above research studies Gao et al [13]also studied the influence of working face conditions andstructures of the ranging arm of the shearer on the drum coalloading rate by DEM simulation Bołoz [14] designed a typeof longwall shearer which was applicable to mining thinhard coal seams and this shearer operation technology andpossible daily output achievement were introduced in hisstudy in detail In 2015 Wydro [15] researched the influ-ences of filling rate and coal plate on the transport rate of thebulk coal with the help of a self-developed drum test benchfor coal transport In 2016 the coal loading process of ashearer was simulated by Gospodarczyk [16] using PFC3Dand the drum transport effect and coal particle movementsunder circumstances of cutting top coal cutting bottom coaland with and without the coal plate were studied

In order to study the complex transportation process ofbulk materials better Cundall and Strack [17 18] put for-ward the DEM for the first time With the development ofnumerical simulation technology the DEM has been widelyused in the fields of bulk material transportation materialscreening rock cutting rock crushing pharmaceutical en-gineering and fluidized bed [19ndash22] Meanwhile manyscholars have also completed the design and performanceanalysis of complex mechanical structures such as feeder[23] chain conveyor [24] and belt conveyor [25] Potyondyand Cundall [26] proposed that the DEM can simulate thebulk properties of the real coal rock after crushing and thecrushed coal rock had the properties of the granular ma-terial so the DEM can be applied to the analysis of the coalloading performance of the drum Dai et al [27] performedthe uniaxial and triaxial numerical simulations of seafloormassive sulfides by leveraging the PFC3D code and pre-dicted the maximum force on the cutting pick Li et al [28]studied the drum cutting properties through DEM simu-lations and concluded that the DEM is an easier faster andreasonable method in the prediction of drum cutting loadand design of the shearer drum Furthermore Gao [29]combined the experimental research and the DEM simu-lation to study the influence of the helix angle of the blade on

the coal loading performance and proved the accuracy andfeasibility of the DEM in the simulation of coal conveyingprocess of the drum

Several scholars have conducted considerable researchstudies with experimental verification and DEM simula-tion on factors affecting the coal loading performance ofthe drum including motion parameters (rotational speedand hauling speed) and structure parameters (the numberand helix angle of blades and web depth) of the drum butthe research about the influence of the structure of the hubon the coal loading performance was not reportedStudying the coal conveying performance of the drumwith the experimental method was high cost and themacroscopic appearance could be observed merely whilethe essence of influences in complexity at a microlevelcould not be revealed +erefore this paper studied thecoal loading rate the three-direction velocity of coalparticles the number of particles in different web depthsand the contact force of particles under different struc-tures of the drum hub by the DEM In the results of thispaper the influence of the hub form and structures andthe rotational speed of the drum on the coal loading rateand the coal particle conveying process was obtained andthe character of these complex influences was discussedand analyzed +is study provides a reference and guid-ance for the design of the drum hub and the workingparameter selection of the shearer in the complex workingenvironment such as thin coal seams

2 Methodology

+e DEM has been applied in different fields by manyscholars worldwide to solve many complex engineeringproblems According to the research content of this paperthe coal face is a cohesive body with continuous propertybefore crushing and then the broken coal can be regarded asa loose material with discrete property after crushing +ebonding model proposed by Potyondy and Cundall [26] cansimulate the continuity of the coal before breaking so thebonding model is selected as the model of building the coalface in the DEM In order to describe the contact force anddisplacement between particles and the relative movementof particles the linear contact model and the sliding modelare selected in the DEM

21 Linear Contact Model +e relationship between parti-cles of normal contact force shear contact force and dis-placement in the linear contact model can be expressed asfollows

Fni KnUnni

ΔFsi minusKsΔUs

i 1113896 (1)

where Fni is the normal contact force Fs

i is the shear contactforce Un is the tangential displacement increment Us

i is theshear component of the contact displacement-incrementvector Kn is the normal contact stiffness Ks is the shearcontact stiffness ni is the unit normal vector of particles andi is the number of particles

2 Complexity

+e normal contact stiffness can be expressed as follows

Kn

k[A]

n k[B]n

k[A]n + k

[B]n

(2)

where k[A]n and k[B]

n are the normal stiffness of two contactparticles

+e shear contact stiffness can be expressed as follows

Ks

k[A]

s k[B]s

k[A]s + k

[B]s

(3)

where k[A]s and k[B]

s are the normal stiffness of two contactparticles

22 SlipModel +e slip is enforced by verifying whether themaximum static friction force is exceeded by the shearingforce +e maximum static friction force is calculated usingthe minimum friction coefficient μ and this friction forcecan be expressed as follows

Fsmax μ F

ni

11138681113868111386811138681113868111386811138681113868 (4)

+e slip will occur between the two contact particleswhen the shear contact force Fs

i meets |Fsi |gtFs

max in equation(4)

23 Bonding Model +e bonding model is mainly used todetermine the contact between two particles before the coalface is broken Since this paper mainly studied the cutoff coalparticle conveying performance of the drum the normal andthe tangential bonding strength between the particles onlyneed to ensure that the coal face can maintain a staticstructure during the cutting process When the force exertedon the particles in the normal and tangential directionexceeds the tensile or tangential bond strength the bondbetween particles breaks and the particles are cut off +econstitutive behavior for contact occurring at a point isindicated in Figure 1

+e fatigue failure criterion of two bonding models canbe expressed as follows

Fcn geRn

Fcs geRs

1113896 (5)

where Rn and Rs are the normal and the tangential bondingstrength of the particles respectively

3 Simulation Model Establishment

In an ideal coal mining process the coal cutoff from the coalface could be loaded by the drum onto the middle chute ofthe conveyor and transported out of the working faceHowever some of the fallen coal were thrown to the goaf andbecame the floating coal In addition some other fallen coalpiled up in the area between the coal face and the chainconveyor due to the insufficient axial velocity and led to anegative impact on the move of the conveyor towards thecoal face Based on the above problems the effect of thedrum on particle ejection speed and axial velocity has animportant impact on the coal loading performance In

addition to the influence of the motion parameters and thestructure parameters of the vane the structure parameters ofthe hub also play an important role in affecting the motionbehavior of particles +erefore four drums with the conicalhub were designed on the basis of the cylinder hub drum asshown in Figure 2 (I) (II) (III) (IV) and (V) whereΨ is thecone angle of the hub but the conical hub leads to a lowerdrum space capacity to a certain extent so three drums withthe curve-shaped hub were designed as shown in Figure 2(VI) (VII) and (VIII) where Ki is the average curvature ofthe hub+e curve-shaped hub drums not only increased theaxial velocity of coal particles but also provided the biggerdrum space capacity and the parameters of the drum hubare shown in Table 1 As one of the motion parameters of thedrum the rotational speed has important and compleximpacts on the loading performance of the drum+ereforethis paper studied the coal loading performance of the drumcombined with the effects of structures of the drum hub andthe rotational speed and the optimal matching relationshipbetween the rotational speed and hub structures wasobtained

+e equipment on the underground coal miningworking face and the numerical simulation model are il-lustrated in Figure 3(a) +e equipment of the coal miningworking face is mainly composed of a shearer a hydraulicsupport and a chain conveyor for coal cutting and loadingsupporting the roof and transportation respectively As themain research object the drum model was established insimulation Additionally it has been proved that the rangingarm of the shearer and the relative position relationshipbetween the chain conveyor and the drum have a significanteffect on the coal loading rate [13 30] so the ranging armand the chain conveyor model were also established insimulation In order to reduce simulation time and simplifythe model the hydraulic support which would not affect thesimulation result was not established In the working processof the drum its rotation direction includes from the rooftowards the floor and from the floor towards the roofcorresponding to two coal loadingmethods of drum pushingand drum ejection as shown in Figure 3(b) Figure 4 showsthe comparison of the coal loading rate of different drumswith drum pushing and ejection and the results of the coalloading rate of drum (I) with drum pushing and ejectionunder different rotational speeds It can be seen that the coalloading rate with the drum ejection method was better thanthat of the drum pushing method obviously In the processof mining thin coal seam the coal cutting and loadingmainly depend on the front drum+erefore this paper onlyfocused on the coal loading performance with the drumejection method

+e particle and material parameters in the simulationare shown in Table 2 +e parameters of the drum structuresweb depth diameter of the loading vane helix angle and thediameter of the hub were 650mm 800mm 23deg and400mm respectively In order to study the loaded coalparticles with different web depths the coal face particleswere dyed according to web depth in which the width ofgreen red blue and yellow particles was 150mm and thewidth of orange particles was 50mm In the simulation

Complexity 3

process the coal falling area was divided into three parts+egoaf was area I the area between the middle chute of thechain conveyor and the coal face was area II and the middlechute of the chain conveyor was area III which is the sta-tistical area of loaded particles +e coal loading rate was theratio of the loaded coal particle mass in area III and the total

fallen coal particle mass as shown in Figure 5 Due to theinteraction between the drum and the coal particles in thecoal loading process the movement of the coal particlesshowed randomness and complexity In order to reveal thecoal loading mechanism and the drum-particle interactionmechanism of drums with different hubs the number and

Ftangential

Fnormalks

kn

PiR

Dashpot

Pj R

Dashpot

μ

(a)

Bond breaks

Bond breaks

Fcn

FcsTensionkbnkbs

l l

Shear

Un(Us)Compression

(b)

Figure 1 (a) +e particle contact model in the DEM (b) constitutive behavior in the contact bonding model

ψ = 90deg ψ = 95deg ψ = 100deg ψ = 105deg

ψ = 110degψ = 110deg

ψ = 105degψ = 100deg

ψ = 100degψ = 100deg

ψ = 90degψ = 90degψ = 95deg

ψ = 95deg

K1 K2 K3K1

K2 K3K1 K2 K3

Figure 2 +e drums with different forms and structures of the hub

Table 1 +e structure parameters of the drum hub

Drum I II III IV V VI VII VIII

Ψ (deg)Ki 90 95 100 105 110K1 1638eminus 1K2 1001eminus 1

K3 0

K1 1224eminus 1K2 7984eminus 2K3 2735eminus 2

K1 1017eminus 1K2 5401eminus 2

K3 0

4 Complexity

velocity of particles at different positions inside the drumwere counted Hence based on each cut line of the pick onthe vane the envelop zone of the loading vane was used asthe statistical zone and the width of the hub was dividedinto five equal zones as shown in Figure 6 so as to ensurethat each statistical zone had the same amount of particlescut from the coal face in unit time Furthermore the right

half of the drum and the coal face formed a closed areawhile the left half was an open area and the vanes mainlyinteract with the particles in the right half of the drum Inorder to study the contact force and the conveying per-formance of particles inside the drum the right half of thedrum was divided into two equal statistical areas as shownin Figure 6

ShearerCoal face

Drum

Ranging arm

Hydraulic supportChain conveyor

Roof

DrumRanging arm

Chain conveyor

Coal face

(a)

Coal loading with drum ejection

Direction ofdrum rotation

from floortowards roof

Hauling direction

Hauling direction

Coal loading with drum pushing

Direction ofdrum rotation

from rooftowards floor

(b)

Figure 3 (a) Shearer in operation (b) the coal loading process of the drum in simulation

Drum I with pushing

Drum I with ejection

Coal loading with drumpushingCoal loading with drumejection

II III IV V VI VII VIIIIDrum

35

40

45

50

55

60

65

Coa

l loa

ding

rate

()

40 60 80 100Rotational speed (rpm)

Figure 4 +e comparison of different coal loading methods

Table 2 +e parameters of the particle in the simulation

Density (kgm3) Poissonrsquos ratio Youngrsquos modulus (GPa)Coal 1400 028 425Steel 7800 030 206

Coefficient of restitution Coefficient of static friction Coefficient of rolling frictionCoal-coal 050 080 010Coal-steel 050 060 005

Complexity 5

4 Analysis of the Simulation Resultsand Discussion

41 e Influence of the Rotational Speed and the HubStructure on Coal Particle Velocities in ree DirectionsIn the simulation process the hauling speed of the drum wasset to 4mmin and the rotational speed was 40 rpm 60 rpm80 rpm and 100 rpm respectively +e velocities of particlesinfluenced by the combination of drum hub structures androtational speed were studied Figure 7 demonstrates thevariation curves of the coal loading rate of eight drums withrotational speed For different matching of the hub struc-tures and drum rotational speed the relationship betweenthe particle velocities and the coal loading rate has beenshown in Table 3 and Figure 8

As indicated in Figure 7 with the increase of the value ofΨ the rotational speed required for the drum to obtain thebest coal loading performance decreases In the case of the

same rotational speed the particle velocity under differentdrums in X and Z directions was not different signifi-cantly while that in the Y direction namely the axialdirection was significantly different as shown in Figure 8and Table 3 +e axial velocity of particles increased withthe increase of the value of Ψ and the lower the rotationalspeed the more obvious the difference When the rota-tional speed increased from 40 rpm to 100 rpm the ve-locity difference in the Y direction between drums (V) and(I) decreased from four times higher to two times +ereason for that was when the rotational speed was smallthe packing density of particles inside the drum was largeand the hub had an obvious impact on the particles Withthe increase of the rotational speed the packing density ofparticles inside the drum decreases which leads to thedecrease of contact between the hub and particles and thevanes gradually played a leading role resulting in thereduction of the velocity difference In the case of the same

Z

X

Y

Area I

Area II

Area III

Area I goafArea II the areabetween coal face andchain conveyor

Area III the effectiveloading area in chute ofchain conveyor

Figure 5 Statistical area division of coal loading

A B C DE

Z

Y1

2

X

View A

n

1

2

Z

X

Hauling direction

View A

(a)

1

2

3

4

5

1

Vane

A

B

C

D

E

2Pick

A-B

B-C

C-D

D-E

Expanded viewπ2 ndashπ2

(b)

Figure 6 +e statistical zone of the drum with different web depths (a) View A (b) Expanded view

6 Complexity

drum the particle velocity in directions Y and Z increasedwith the increase of the rotational speed while the velocityin the X direction decreased +is is because with theincrease of the rotational speed the action of the vaneswas more obvious and the number and amplitude of thethrown particles increased correspondingly which led to

the increase of the particle velocity in Y and Z directions toan extent Due to the influence of the vanes more particleswere thrown from the right half of the drum to the lefthalf and the movement direction was reversed in the Xdirection resulting in a decrease in the velocity in the Xdirection to some extent

60 80 10040Rotational speed (rpm)

45

50

55

60

65

Coa

l loa

ding

rate

()

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Figure 7 +e coal loading rate curve of eight drums at different rotational speeds

Table 3 +e statistical analysis of particle velocities in three directions and coal loading rate

n (rpm) Drum X direction (ms) Y direction (ms) Z direction (ms) Loading rate ()

40

I 0185 0126 0198 4819II 0243 0209 0217 5275III 0239 0332 0230 5646IV 0219 0371 0244 5590V 0241 0459 0238 5153VI 0288 0464 0266 5667VII 0265 0368 0333 6277VIII 0245 0238 0229 5711

60

I 0276 0200 0211 4999II 0279 0286 0262 5591III 0281 0391 0250 6033IV 0267 0469 0139 5477V 0261 0538 0254 5063VI 0337 0554 0290 5870VII 0333 0462 0317 5948VIII 0261 0319 0234 5877

80

I 0437 0308 0245 5068II 0402 0393 0237 5174III 0461 0511 0283 5424IV 0424 0572 0221 5195V 0429 0680 0211 4844VI 0544 0673 0230 5788VII 0547 0573 0284 5724VIII 0483 0380 0219 5654

100

I 0531 0344 0144 4587II 0546 0430 0190 4825III 0573 0554 0133 5156IV 0577 0621 0138 4957V 0673 0746 0143 4800VI 0691 0722 0128 5375VII 0596 0591 0162 5440VIII 0487 0427 0148 5374

Complexity 7

+e coal loading performance of the drum depends onthe axial velocity of particles to a large extent +rough theanalysis of Table 3 and Figure 8 the axial velocity of particlesand the coal loading rate of the drum increase with theincrease in the value of Ψ but when Ψgt100deg with the in-crease in the value of Ψ the axial velocity of particles stillincreases while the coal loading rate decreases +e reasonfor that is the average diameter of the hub was too large dueto the excessive cone angle and the particles in the drumwere compressed by the hub and fell into area II in the formof extrusion Additionally the axial velocity of particles indrums (VI) (VII) and (VIII) was close to that of drums (V)(IV) and (II) respectively However the diameter of thecurve-shaped hub is smaller than that of the conical hub so

the squeezing effect of the particles by the hub was smallerwhich led to a higher coal loading rate

42 e Influence of the Drum Space Capacity on the CoalConveying Performance +e drum space capacity dependson the diameter of the vane and the hub +e cone angle ofthe hub has a negative impact on the drum space capacityespecially in the case of the lower rotational speed and thecoal cutting rate of the drum is bigger than the conveyingflow rate which is prone to clogging +e theoretical con-veying flow of the drum depends on the axial velocity ofparticles and the swept area by vanes which is expressed byequation (6) +e cutting rate of the drum is determined by

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

00

01

02

03

04

05

06M

ean

velo

city

of p

artic

les (

ms

)

48

51

54

57

60

63

Coa

l loa

ding

rate

()

IIIII IV V VII VIIIVIIDrum

(a)

00

01

02

03

04

05

06

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

48

51

54

57

60

Coa

l loa

ding

rate

()

(b)

48

51

54

57

60

Coa

l loa

ding

rate

()

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

(c)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08M

ean

velo

city

of p

artic

les (

ms

)

45

48

51

54

57

Coa

l loa

ding

rate

()

(d)

Figure 8+e relationship between particle velocity in three directions and loading rate at different rotational speeds (a) 40 rpm (b) 60 rpm(c) 80 rpm and (d) 100 rpm

8 Complexity

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 3: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

+e normal contact stiffness can be expressed as follows

Kn

k[A]

n k[B]n

k[A]n + k

[B]n

(2)

where k[A]n and k[B]

n are the normal stiffness of two contactparticles

+e shear contact stiffness can be expressed as follows

Ks

k[A]

s k[B]s

k[A]s + k

[B]s

(3)

where k[A]s and k[B]

s are the normal stiffness of two contactparticles

22 SlipModel +e slip is enforced by verifying whether themaximum static friction force is exceeded by the shearingforce +e maximum static friction force is calculated usingthe minimum friction coefficient μ and this friction forcecan be expressed as follows

Fsmax μ F

ni

11138681113868111386811138681113868111386811138681113868 (4)

+e slip will occur between the two contact particleswhen the shear contact force Fs

i meets |Fsi |gtFs

max in equation(4)

23 Bonding Model +e bonding model is mainly used todetermine the contact between two particles before the coalface is broken Since this paper mainly studied the cutoff coalparticle conveying performance of the drum the normal andthe tangential bonding strength between the particles onlyneed to ensure that the coal face can maintain a staticstructure during the cutting process When the force exertedon the particles in the normal and tangential directionexceeds the tensile or tangential bond strength the bondbetween particles breaks and the particles are cut off +econstitutive behavior for contact occurring at a point isindicated in Figure 1

+e fatigue failure criterion of two bonding models canbe expressed as follows

Fcn geRn

Fcs geRs

1113896 (5)

where Rn and Rs are the normal and the tangential bondingstrength of the particles respectively

3 Simulation Model Establishment

In an ideal coal mining process the coal cutoff from the coalface could be loaded by the drum onto the middle chute ofthe conveyor and transported out of the working faceHowever some of the fallen coal were thrown to the goaf andbecame the floating coal In addition some other fallen coalpiled up in the area between the coal face and the chainconveyor due to the insufficient axial velocity and led to anegative impact on the move of the conveyor towards thecoal face Based on the above problems the effect of thedrum on particle ejection speed and axial velocity has animportant impact on the coal loading performance In

addition to the influence of the motion parameters and thestructure parameters of the vane the structure parameters ofthe hub also play an important role in affecting the motionbehavior of particles +erefore four drums with the conicalhub were designed on the basis of the cylinder hub drum asshown in Figure 2 (I) (II) (III) (IV) and (V) whereΨ is thecone angle of the hub but the conical hub leads to a lowerdrum space capacity to a certain extent so three drums withthe curve-shaped hub were designed as shown in Figure 2(VI) (VII) and (VIII) where Ki is the average curvature ofthe hub+e curve-shaped hub drums not only increased theaxial velocity of coal particles but also provided the biggerdrum space capacity and the parameters of the drum hubare shown in Table 1 As one of the motion parameters of thedrum the rotational speed has important and compleximpacts on the loading performance of the drum+ereforethis paper studied the coal loading performance of the drumcombined with the effects of structures of the drum hub andthe rotational speed and the optimal matching relationshipbetween the rotational speed and hub structures wasobtained

+e equipment on the underground coal miningworking face and the numerical simulation model are il-lustrated in Figure 3(a) +e equipment of the coal miningworking face is mainly composed of a shearer a hydraulicsupport and a chain conveyor for coal cutting and loadingsupporting the roof and transportation respectively As themain research object the drum model was established insimulation Additionally it has been proved that the rangingarm of the shearer and the relative position relationshipbetween the chain conveyor and the drum have a significanteffect on the coal loading rate [13 30] so the ranging armand the chain conveyor model were also established insimulation In order to reduce simulation time and simplifythe model the hydraulic support which would not affect thesimulation result was not established In the working processof the drum its rotation direction includes from the rooftowards the floor and from the floor towards the roofcorresponding to two coal loadingmethods of drum pushingand drum ejection as shown in Figure 3(b) Figure 4 showsthe comparison of the coal loading rate of different drumswith drum pushing and ejection and the results of the coalloading rate of drum (I) with drum pushing and ejectionunder different rotational speeds It can be seen that the coalloading rate with the drum ejection method was better thanthat of the drum pushing method obviously In the processof mining thin coal seam the coal cutting and loadingmainly depend on the front drum+erefore this paper onlyfocused on the coal loading performance with the drumejection method

+e particle and material parameters in the simulationare shown in Table 2 +e parameters of the drum structuresweb depth diameter of the loading vane helix angle and thediameter of the hub were 650mm 800mm 23deg and400mm respectively In order to study the loaded coalparticles with different web depths the coal face particleswere dyed according to web depth in which the width ofgreen red blue and yellow particles was 150mm and thewidth of orange particles was 50mm In the simulation

Complexity 3

process the coal falling area was divided into three parts+egoaf was area I the area between the middle chute of thechain conveyor and the coal face was area II and the middlechute of the chain conveyor was area III which is the sta-tistical area of loaded particles +e coal loading rate was theratio of the loaded coal particle mass in area III and the total

fallen coal particle mass as shown in Figure 5 Due to theinteraction between the drum and the coal particles in thecoal loading process the movement of the coal particlesshowed randomness and complexity In order to reveal thecoal loading mechanism and the drum-particle interactionmechanism of drums with different hubs the number and

Ftangential

Fnormalks

kn

PiR

Dashpot

Pj R

Dashpot

μ

(a)

Bond breaks

Bond breaks

Fcn

FcsTensionkbnkbs

l l

Shear

Un(Us)Compression

(b)

Figure 1 (a) +e particle contact model in the DEM (b) constitutive behavior in the contact bonding model

ψ = 90deg ψ = 95deg ψ = 100deg ψ = 105deg

ψ = 110degψ = 110deg

ψ = 105degψ = 100deg

ψ = 100degψ = 100deg

ψ = 90degψ = 90degψ = 95deg

ψ = 95deg

K1 K2 K3K1

K2 K3K1 K2 K3

Figure 2 +e drums with different forms and structures of the hub

Table 1 +e structure parameters of the drum hub

Drum I II III IV V VI VII VIII

Ψ (deg)Ki 90 95 100 105 110K1 1638eminus 1K2 1001eminus 1

K3 0

K1 1224eminus 1K2 7984eminus 2K3 2735eminus 2

K1 1017eminus 1K2 5401eminus 2

K3 0

4 Complexity

velocity of particles at different positions inside the drumwere counted Hence based on each cut line of the pick onthe vane the envelop zone of the loading vane was used asthe statistical zone and the width of the hub was dividedinto five equal zones as shown in Figure 6 so as to ensurethat each statistical zone had the same amount of particlescut from the coal face in unit time Furthermore the right

half of the drum and the coal face formed a closed areawhile the left half was an open area and the vanes mainlyinteract with the particles in the right half of the drum Inorder to study the contact force and the conveying per-formance of particles inside the drum the right half of thedrum was divided into two equal statistical areas as shownin Figure 6

ShearerCoal face

Drum

Ranging arm

Hydraulic supportChain conveyor

Roof

DrumRanging arm

Chain conveyor

Coal face

(a)

Coal loading with drum ejection

Direction ofdrum rotation

from floortowards roof

Hauling direction

Hauling direction

Coal loading with drum pushing

Direction ofdrum rotation

from rooftowards floor

(b)

Figure 3 (a) Shearer in operation (b) the coal loading process of the drum in simulation

Drum I with pushing

Drum I with ejection

Coal loading with drumpushingCoal loading with drumejection

II III IV V VI VII VIIIIDrum

35

40

45

50

55

60

65

Coa

l loa

ding

rate

()

40 60 80 100Rotational speed (rpm)

Figure 4 +e comparison of different coal loading methods

Table 2 +e parameters of the particle in the simulation

Density (kgm3) Poissonrsquos ratio Youngrsquos modulus (GPa)Coal 1400 028 425Steel 7800 030 206

Coefficient of restitution Coefficient of static friction Coefficient of rolling frictionCoal-coal 050 080 010Coal-steel 050 060 005

Complexity 5

4 Analysis of the Simulation Resultsand Discussion

41 e Influence of the Rotational Speed and the HubStructure on Coal Particle Velocities in ree DirectionsIn the simulation process the hauling speed of the drum wasset to 4mmin and the rotational speed was 40 rpm 60 rpm80 rpm and 100 rpm respectively +e velocities of particlesinfluenced by the combination of drum hub structures androtational speed were studied Figure 7 demonstrates thevariation curves of the coal loading rate of eight drums withrotational speed For different matching of the hub struc-tures and drum rotational speed the relationship betweenthe particle velocities and the coal loading rate has beenshown in Table 3 and Figure 8

As indicated in Figure 7 with the increase of the value ofΨ the rotational speed required for the drum to obtain thebest coal loading performance decreases In the case of the

same rotational speed the particle velocity under differentdrums in X and Z directions was not different signifi-cantly while that in the Y direction namely the axialdirection was significantly different as shown in Figure 8and Table 3 +e axial velocity of particles increased withthe increase of the value of Ψ and the lower the rotationalspeed the more obvious the difference When the rota-tional speed increased from 40 rpm to 100 rpm the ve-locity difference in the Y direction between drums (V) and(I) decreased from four times higher to two times +ereason for that was when the rotational speed was smallthe packing density of particles inside the drum was largeand the hub had an obvious impact on the particles Withthe increase of the rotational speed the packing density ofparticles inside the drum decreases which leads to thedecrease of contact between the hub and particles and thevanes gradually played a leading role resulting in thereduction of the velocity difference In the case of the same

Z

X

Y

Area I

Area II

Area III

Area I goafArea II the areabetween coal face andchain conveyor

Area III the effectiveloading area in chute ofchain conveyor

Figure 5 Statistical area division of coal loading

A B C DE

Z

Y1

2

X

View A

n

1

2

Z

X

Hauling direction

View A

(a)

1

2

3

4

5

1

Vane

A

B

C

D

E

2Pick

A-B

B-C

C-D

D-E

Expanded viewπ2 ndashπ2

(b)

Figure 6 +e statistical zone of the drum with different web depths (a) View A (b) Expanded view

6 Complexity

drum the particle velocity in directions Y and Z increasedwith the increase of the rotational speed while the velocityin the X direction decreased +is is because with theincrease of the rotational speed the action of the vaneswas more obvious and the number and amplitude of thethrown particles increased correspondingly which led to

the increase of the particle velocity in Y and Z directions toan extent Due to the influence of the vanes more particleswere thrown from the right half of the drum to the lefthalf and the movement direction was reversed in the Xdirection resulting in a decrease in the velocity in the Xdirection to some extent

60 80 10040Rotational speed (rpm)

45

50

55

60

65

Coa

l loa

ding

rate

()

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Figure 7 +e coal loading rate curve of eight drums at different rotational speeds

Table 3 +e statistical analysis of particle velocities in three directions and coal loading rate

n (rpm) Drum X direction (ms) Y direction (ms) Z direction (ms) Loading rate ()

40

I 0185 0126 0198 4819II 0243 0209 0217 5275III 0239 0332 0230 5646IV 0219 0371 0244 5590V 0241 0459 0238 5153VI 0288 0464 0266 5667VII 0265 0368 0333 6277VIII 0245 0238 0229 5711

60

I 0276 0200 0211 4999II 0279 0286 0262 5591III 0281 0391 0250 6033IV 0267 0469 0139 5477V 0261 0538 0254 5063VI 0337 0554 0290 5870VII 0333 0462 0317 5948VIII 0261 0319 0234 5877

80

I 0437 0308 0245 5068II 0402 0393 0237 5174III 0461 0511 0283 5424IV 0424 0572 0221 5195V 0429 0680 0211 4844VI 0544 0673 0230 5788VII 0547 0573 0284 5724VIII 0483 0380 0219 5654

100

I 0531 0344 0144 4587II 0546 0430 0190 4825III 0573 0554 0133 5156IV 0577 0621 0138 4957V 0673 0746 0143 4800VI 0691 0722 0128 5375VII 0596 0591 0162 5440VIII 0487 0427 0148 5374

Complexity 7

+e coal loading performance of the drum depends onthe axial velocity of particles to a large extent +rough theanalysis of Table 3 and Figure 8 the axial velocity of particlesand the coal loading rate of the drum increase with theincrease in the value of Ψ but when Ψgt100deg with the in-crease in the value of Ψ the axial velocity of particles stillincreases while the coal loading rate decreases +e reasonfor that is the average diameter of the hub was too large dueto the excessive cone angle and the particles in the drumwere compressed by the hub and fell into area II in the formof extrusion Additionally the axial velocity of particles indrums (VI) (VII) and (VIII) was close to that of drums (V)(IV) and (II) respectively However the diameter of thecurve-shaped hub is smaller than that of the conical hub so

the squeezing effect of the particles by the hub was smallerwhich led to a higher coal loading rate

42 e Influence of the Drum Space Capacity on the CoalConveying Performance +e drum space capacity dependson the diameter of the vane and the hub +e cone angle ofthe hub has a negative impact on the drum space capacityespecially in the case of the lower rotational speed and thecoal cutting rate of the drum is bigger than the conveyingflow rate which is prone to clogging +e theoretical con-veying flow of the drum depends on the axial velocity ofparticles and the swept area by vanes which is expressed byequation (6) +e cutting rate of the drum is determined by

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

00

01

02

03

04

05

06M

ean

velo

city

of p

artic

les (

ms

)

48

51

54

57

60

63

Coa

l loa

ding

rate

()

IIIII IV V VII VIIIVIIDrum

(a)

00

01

02

03

04

05

06

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

48

51

54

57

60

Coa

l loa

ding

rate

()

(b)

48

51

54

57

60

Coa

l loa

ding

rate

()

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

(c)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08M

ean

velo

city

of p

artic

les (

ms

)

45

48

51

54

57

Coa

l loa

ding

rate

()

(d)

Figure 8+e relationship between particle velocity in three directions and loading rate at different rotational speeds (a) 40 rpm (b) 60 rpm(c) 80 rpm and (d) 100 rpm

8 Complexity

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 4: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

process the coal falling area was divided into three parts+egoaf was area I the area between the middle chute of thechain conveyor and the coal face was area II and the middlechute of the chain conveyor was area III which is the sta-tistical area of loaded particles +e coal loading rate was theratio of the loaded coal particle mass in area III and the total

fallen coal particle mass as shown in Figure 5 Due to theinteraction between the drum and the coal particles in thecoal loading process the movement of the coal particlesshowed randomness and complexity In order to reveal thecoal loading mechanism and the drum-particle interactionmechanism of drums with different hubs the number and

Ftangential

Fnormalks

kn

PiR

Dashpot

Pj R

Dashpot

μ

(a)

Bond breaks

Bond breaks

Fcn

FcsTensionkbnkbs

l l

Shear

Un(Us)Compression

(b)

Figure 1 (a) +e particle contact model in the DEM (b) constitutive behavior in the contact bonding model

ψ = 90deg ψ = 95deg ψ = 100deg ψ = 105deg

ψ = 110degψ = 110deg

ψ = 105degψ = 100deg

ψ = 100degψ = 100deg

ψ = 90degψ = 90degψ = 95deg

ψ = 95deg

K1 K2 K3K1

K2 K3K1 K2 K3

Figure 2 +e drums with different forms and structures of the hub

Table 1 +e structure parameters of the drum hub

Drum I II III IV V VI VII VIII

Ψ (deg)Ki 90 95 100 105 110K1 1638eminus 1K2 1001eminus 1

K3 0

K1 1224eminus 1K2 7984eminus 2K3 2735eminus 2

K1 1017eminus 1K2 5401eminus 2

K3 0

4 Complexity

velocity of particles at different positions inside the drumwere counted Hence based on each cut line of the pick onthe vane the envelop zone of the loading vane was used asthe statistical zone and the width of the hub was dividedinto five equal zones as shown in Figure 6 so as to ensurethat each statistical zone had the same amount of particlescut from the coal face in unit time Furthermore the right

half of the drum and the coal face formed a closed areawhile the left half was an open area and the vanes mainlyinteract with the particles in the right half of the drum Inorder to study the contact force and the conveying per-formance of particles inside the drum the right half of thedrum was divided into two equal statistical areas as shownin Figure 6

ShearerCoal face

Drum

Ranging arm

Hydraulic supportChain conveyor

Roof

DrumRanging arm

Chain conveyor

Coal face

(a)

Coal loading with drum ejection

Direction ofdrum rotation

from floortowards roof

Hauling direction

Hauling direction

Coal loading with drum pushing

Direction ofdrum rotation

from rooftowards floor

(b)

Figure 3 (a) Shearer in operation (b) the coal loading process of the drum in simulation

Drum I with pushing

Drum I with ejection

Coal loading with drumpushingCoal loading with drumejection

II III IV V VI VII VIIIIDrum

35

40

45

50

55

60

65

Coa

l loa

ding

rate

()

40 60 80 100Rotational speed (rpm)

Figure 4 +e comparison of different coal loading methods

Table 2 +e parameters of the particle in the simulation

Density (kgm3) Poissonrsquos ratio Youngrsquos modulus (GPa)Coal 1400 028 425Steel 7800 030 206

Coefficient of restitution Coefficient of static friction Coefficient of rolling frictionCoal-coal 050 080 010Coal-steel 050 060 005

Complexity 5

4 Analysis of the Simulation Resultsand Discussion

41 e Influence of the Rotational Speed and the HubStructure on Coal Particle Velocities in ree DirectionsIn the simulation process the hauling speed of the drum wasset to 4mmin and the rotational speed was 40 rpm 60 rpm80 rpm and 100 rpm respectively +e velocities of particlesinfluenced by the combination of drum hub structures androtational speed were studied Figure 7 demonstrates thevariation curves of the coal loading rate of eight drums withrotational speed For different matching of the hub struc-tures and drum rotational speed the relationship betweenthe particle velocities and the coal loading rate has beenshown in Table 3 and Figure 8

As indicated in Figure 7 with the increase of the value ofΨ the rotational speed required for the drum to obtain thebest coal loading performance decreases In the case of the

same rotational speed the particle velocity under differentdrums in X and Z directions was not different signifi-cantly while that in the Y direction namely the axialdirection was significantly different as shown in Figure 8and Table 3 +e axial velocity of particles increased withthe increase of the value of Ψ and the lower the rotationalspeed the more obvious the difference When the rota-tional speed increased from 40 rpm to 100 rpm the ve-locity difference in the Y direction between drums (V) and(I) decreased from four times higher to two times +ereason for that was when the rotational speed was smallthe packing density of particles inside the drum was largeand the hub had an obvious impact on the particles Withthe increase of the rotational speed the packing density ofparticles inside the drum decreases which leads to thedecrease of contact between the hub and particles and thevanes gradually played a leading role resulting in thereduction of the velocity difference In the case of the same

Z

X

Y

Area I

Area II

Area III

Area I goafArea II the areabetween coal face andchain conveyor

Area III the effectiveloading area in chute ofchain conveyor

Figure 5 Statistical area division of coal loading

A B C DE

Z

Y1

2

X

View A

n

1

2

Z

X

Hauling direction

View A

(a)

1

2

3

4

5

1

Vane

A

B

C

D

E

2Pick

A-B

B-C

C-D

D-E

Expanded viewπ2 ndashπ2

(b)

Figure 6 +e statistical zone of the drum with different web depths (a) View A (b) Expanded view

6 Complexity

drum the particle velocity in directions Y and Z increasedwith the increase of the rotational speed while the velocityin the X direction decreased +is is because with theincrease of the rotational speed the action of the vaneswas more obvious and the number and amplitude of thethrown particles increased correspondingly which led to

the increase of the particle velocity in Y and Z directions toan extent Due to the influence of the vanes more particleswere thrown from the right half of the drum to the lefthalf and the movement direction was reversed in the Xdirection resulting in a decrease in the velocity in the Xdirection to some extent

60 80 10040Rotational speed (rpm)

45

50

55

60

65

Coa

l loa

ding

rate

()

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Figure 7 +e coal loading rate curve of eight drums at different rotational speeds

Table 3 +e statistical analysis of particle velocities in three directions and coal loading rate

n (rpm) Drum X direction (ms) Y direction (ms) Z direction (ms) Loading rate ()

40

I 0185 0126 0198 4819II 0243 0209 0217 5275III 0239 0332 0230 5646IV 0219 0371 0244 5590V 0241 0459 0238 5153VI 0288 0464 0266 5667VII 0265 0368 0333 6277VIII 0245 0238 0229 5711

60

I 0276 0200 0211 4999II 0279 0286 0262 5591III 0281 0391 0250 6033IV 0267 0469 0139 5477V 0261 0538 0254 5063VI 0337 0554 0290 5870VII 0333 0462 0317 5948VIII 0261 0319 0234 5877

80

I 0437 0308 0245 5068II 0402 0393 0237 5174III 0461 0511 0283 5424IV 0424 0572 0221 5195V 0429 0680 0211 4844VI 0544 0673 0230 5788VII 0547 0573 0284 5724VIII 0483 0380 0219 5654

100

I 0531 0344 0144 4587II 0546 0430 0190 4825III 0573 0554 0133 5156IV 0577 0621 0138 4957V 0673 0746 0143 4800VI 0691 0722 0128 5375VII 0596 0591 0162 5440VIII 0487 0427 0148 5374

Complexity 7

+e coal loading performance of the drum depends onthe axial velocity of particles to a large extent +rough theanalysis of Table 3 and Figure 8 the axial velocity of particlesand the coal loading rate of the drum increase with theincrease in the value of Ψ but when Ψgt100deg with the in-crease in the value of Ψ the axial velocity of particles stillincreases while the coal loading rate decreases +e reasonfor that is the average diameter of the hub was too large dueto the excessive cone angle and the particles in the drumwere compressed by the hub and fell into area II in the formof extrusion Additionally the axial velocity of particles indrums (VI) (VII) and (VIII) was close to that of drums (V)(IV) and (II) respectively However the diameter of thecurve-shaped hub is smaller than that of the conical hub so

the squeezing effect of the particles by the hub was smallerwhich led to a higher coal loading rate

42 e Influence of the Drum Space Capacity on the CoalConveying Performance +e drum space capacity dependson the diameter of the vane and the hub +e cone angle ofthe hub has a negative impact on the drum space capacityespecially in the case of the lower rotational speed and thecoal cutting rate of the drum is bigger than the conveyingflow rate which is prone to clogging +e theoretical con-veying flow of the drum depends on the axial velocity ofparticles and the swept area by vanes which is expressed byequation (6) +e cutting rate of the drum is determined by

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

00

01

02

03

04

05

06M

ean

velo

city

of p

artic

les (

ms

)

48

51

54

57

60

63

Coa

l loa

ding

rate

()

IIIII IV V VII VIIIVIIDrum

(a)

00

01

02

03

04

05

06

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

48

51

54

57

60

Coa

l loa

ding

rate

()

(b)

48

51

54

57

60

Coa

l loa

ding

rate

()

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

(c)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08M

ean

velo

city

of p

artic

les (

ms

)

45

48

51

54

57

Coa

l loa

ding

rate

()

(d)

Figure 8+e relationship between particle velocity in three directions and loading rate at different rotational speeds (a) 40 rpm (b) 60 rpm(c) 80 rpm and (d) 100 rpm

8 Complexity

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 5: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

velocity of particles at different positions inside the drumwere counted Hence based on each cut line of the pick onthe vane the envelop zone of the loading vane was used asthe statistical zone and the width of the hub was dividedinto five equal zones as shown in Figure 6 so as to ensurethat each statistical zone had the same amount of particlescut from the coal face in unit time Furthermore the right

half of the drum and the coal face formed a closed areawhile the left half was an open area and the vanes mainlyinteract with the particles in the right half of the drum Inorder to study the contact force and the conveying per-formance of particles inside the drum the right half of thedrum was divided into two equal statistical areas as shownin Figure 6

ShearerCoal face

Drum

Ranging arm

Hydraulic supportChain conveyor

Roof

DrumRanging arm

Chain conveyor

Coal face

(a)

Coal loading with drum ejection

Direction ofdrum rotation

from floortowards roof

Hauling direction

Hauling direction

Coal loading with drum pushing

Direction ofdrum rotation

from rooftowards floor

(b)

Figure 3 (a) Shearer in operation (b) the coal loading process of the drum in simulation

Drum I with pushing

Drum I with ejection

Coal loading with drumpushingCoal loading with drumejection

II III IV V VI VII VIIIIDrum

35

40

45

50

55

60

65

Coa

l loa

ding

rate

()

40 60 80 100Rotational speed (rpm)

Figure 4 +e comparison of different coal loading methods

Table 2 +e parameters of the particle in the simulation

Density (kgm3) Poissonrsquos ratio Youngrsquos modulus (GPa)Coal 1400 028 425Steel 7800 030 206

Coefficient of restitution Coefficient of static friction Coefficient of rolling frictionCoal-coal 050 080 010Coal-steel 050 060 005

Complexity 5

4 Analysis of the Simulation Resultsand Discussion

41 e Influence of the Rotational Speed and the HubStructure on Coal Particle Velocities in ree DirectionsIn the simulation process the hauling speed of the drum wasset to 4mmin and the rotational speed was 40 rpm 60 rpm80 rpm and 100 rpm respectively +e velocities of particlesinfluenced by the combination of drum hub structures androtational speed were studied Figure 7 demonstrates thevariation curves of the coal loading rate of eight drums withrotational speed For different matching of the hub struc-tures and drum rotational speed the relationship betweenthe particle velocities and the coal loading rate has beenshown in Table 3 and Figure 8

As indicated in Figure 7 with the increase of the value ofΨ the rotational speed required for the drum to obtain thebest coal loading performance decreases In the case of the

same rotational speed the particle velocity under differentdrums in X and Z directions was not different signifi-cantly while that in the Y direction namely the axialdirection was significantly different as shown in Figure 8and Table 3 +e axial velocity of particles increased withthe increase of the value of Ψ and the lower the rotationalspeed the more obvious the difference When the rota-tional speed increased from 40 rpm to 100 rpm the ve-locity difference in the Y direction between drums (V) and(I) decreased from four times higher to two times +ereason for that was when the rotational speed was smallthe packing density of particles inside the drum was largeand the hub had an obvious impact on the particles Withthe increase of the rotational speed the packing density ofparticles inside the drum decreases which leads to thedecrease of contact between the hub and particles and thevanes gradually played a leading role resulting in thereduction of the velocity difference In the case of the same

Z

X

Y

Area I

Area II

Area III

Area I goafArea II the areabetween coal face andchain conveyor

Area III the effectiveloading area in chute ofchain conveyor

Figure 5 Statistical area division of coal loading

A B C DE

Z

Y1

2

X

View A

n

1

2

Z

X

Hauling direction

View A

(a)

1

2

3

4

5

1

Vane

A

B

C

D

E

2Pick

A-B

B-C

C-D

D-E

Expanded viewπ2 ndashπ2

(b)

Figure 6 +e statistical zone of the drum with different web depths (a) View A (b) Expanded view

6 Complexity

drum the particle velocity in directions Y and Z increasedwith the increase of the rotational speed while the velocityin the X direction decreased +is is because with theincrease of the rotational speed the action of the vaneswas more obvious and the number and amplitude of thethrown particles increased correspondingly which led to

the increase of the particle velocity in Y and Z directions toan extent Due to the influence of the vanes more particleswere thrown from the right half of the drum to the lefthalf and the movement direction was reversed in the Xdirection resulting in a decrease in the velocity in the Xdirection to some extent

60 80 10040Rotational speed (rpm)

45

50

55

60

65

Coa

l loa

ding

rate

()

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Figure 7 +e coal loading rate curve of eight drums at different rotational speeds

Table 3 +e statistical analysis of particle velocities in three directions and coal loading rate

n (rpm) Drum X direction (ms) Y direction (ms) Z direction (ms) Loading rate ()

40

I 0185 0126 0198 4819II 0243 0209 0217 5275III 0239 0332 0230 5646IV 0219 0371 0244 5590V 0241 0459 0238 5153VI 0288 0464 0266 5667VII 0265 0368 0333 6277VIII 0245 0238 0229 5711

60

I 0276 0200 0211 4999II 0279 0286 0262 5591III 0281 0391 0250 6033IV 0267 0469 0139 5477V 0261 0538 0254 5063VI 0337 0554 0290 5870VII 0333 0462 0317 5948VIII 0261 0319 0234 5877

80

I 0437 0308 0245 5068II 0402 0393 0237 5174III 0461 0511 0283 5424IV 0424 0572 0221 5195V 0429 0680 0211 4844VI 0544 0673 0230 5788VII 0547 0573 0284 5724VIII 0483 0380 0219 5654

100

I 0531 0344 0144 4587II 0546 0430 0190 4825III 0573 0554 0133 5156IV 0577 0621 0138 4957V 0673 0746 0143 4800VI 0691 0722 0128 5375VII 0596 0591 0162 5440VIII 0487 0427 0148 5374

Complexity 7

+e coal loading performance of the drum depends onthe axial velocity of particles to a large extent +rough theanalysis of Table 3 and Figure 8 the axial velocity of particlesand the coal loading rate of the drum increase with theincrease in the value of Ψ but when Ψgt100deg with the in-crease in the value of Ψ the axial velocity of particles stillincreases while the coal loading rate decreases +e reasonfor that is the average diameter of the hub was too large dueto the excessive cone angle and the particles in the drumwere compressed by the hub and fell into area II in the formof extrusion Additionally the axial velocity of particles indrums (VI) (VII) and (VIII) was close to that of drums (V)(IV) and (II) respectively However the diameter of thecurve-shaped hub is smaller than that of the conical hub so

the squeezing effect of the particles by the hub was smallerwhich led to a higher coal loading rate

42 e Influence of the Drum Space Capacity on the CoalConveying Performance +e drum space capacity dependson the diameter of the vane and the hub +e cone angle ofthe hub has a negative impact on the drum space capacityespecially in the case of the lower rotational speed and thecoal cutting rate of the drum is bigger than the conveyingflow rate which is prone to clogging +e theoretical con-veying flow of the drum depends on the axial velocity ofparticles and the swept area by vanes which is expressed byequation (6) +e cutting rate of the drum is determined by

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

00

01

02

03

04

05

06M

ean

velo

city

of p

artic

les (

ms

)

48

51

54

57

60

63

Coa

l loa

ding

rate

()

IIIII IV V VII VIIIVIIDrum

(a)

00

01

02

03

04

05

06

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

48

51

54

57

60

Coa

l loa

ding

rate

()

(b)

48

51

54

57

60

Coa

l loa

ding

rate

()

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

(c)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08M

ean

velo

city

of p

artic

les (

ms

)

45

48

51

54

57

Coa

l loa

ding

rate

()

(d)

Figure 8+e relationship between particle velocity in three directions and loading rate at different rotational speeds (a) 40 rpm (b) 60 rpm(c) 80 rpm and (d) 100 rpm

8 Complexity

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 6: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

4 Analysis of the Simulation Resultsand Discussion

41 e Influence of the Rotational Speed and the HubStructure on Coal Particle Velocities in ree DirectionsIn the simulation process the hauling speed of the drum wasset to 4mmin and the rotational speed was 40 rpm 60 rpm80 rpm and 100 rpm respectively +e velocities of particlesinfluenced by the combination of drum hub structures androtational speed were studied Figure 7 demonstrates thevariation curves of the coal loading rate of eight drums withrotational speed For different matching of the hub struc-tures and drum rotational speed the relationship betweenthe particle velocities and the coal loading rate has beenshown in Table 3 and Figure 8

As indicated in Figure 7 with the increase of the value ofΨ the rotational speed required for the drum to obtain thebest coal loading performance decreases In the case of the

same rotational speed the particle velocity under differentdrums in X and Z directions was not different signifi-cantly while that in the Y direction namely the axialdirection was significantly different as shown in Figure 8and Table 3 +e axial velocity of particles increased withthe increase of the value of Ψ and the lower the rotationalspeed the more obvious the difference When the rota-tional speed increased from 40 rpm to 100 rpm the ve-locity difference in the Y direction between drums (V) and(I) decreased from four times higher to two times +ereason for that was when the rotational speed was smallthe packing density of particles inside the drum was largeand the hub had an obvious impact on the particles Withthe increase of the rotational speed the packing density ofparticles inside the drum decreases which leads to thedecrease of contact between the hub and particles and thevanes gradually played a leading role resulting in thereduction of the velocity difference In the case of the same

Z

X

Y

Area I

Area II

Area III

Area I goafArea II the areabetween coal face andchain conveyor

Area III the effectiveloading area in chute ofchain conveyor

Figure 5 Statistical area division of coal loading

A B C DE

Z

Y1

2

X

View A

n

1

2

Z

X

Hauling direction

View A

(a)

1

2

3

4

5

1

Vane

A

B

C

D

E

2Pick

A-B

B-C

C-D

D-E

Expanded viewπ2 ndashπ2

(b)

Figure 6 +e statistical zone of the drum with different web depths (a) View A (b) Expanded view

6 Complexity

drum the particle velocity in directions Y and Z increasedwith the increase of the rotational speed while the velocityin the X direction decreased +is is because with theincrease of the rotational speed the action of the vaneswas more obvious and the number and amplitude of thethrown particles increased correspondingly which led to

the increase of the particle velocity in Y and Z directions toan extent Due to the influence of the vanes more particleswere thrown from the right half of the drum to the lefthalf and the movement direction was reversed in the Xdirection resulting in a decrease in the velocity in the Xdirection to some extent

60 80 10040Rotational speed (rpm)

45

50

55

60

65

Coa

l loa

ding

rate

()

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Figure 7 +e coal loading rate curve of eight drums at different rotational speeds

Table 3 +e statistical analysis of particle velocities in three directions and coal loading rate

n (rpm) Drum X direction (ms) Y direction (ms) Z direction (ms) Loading rate ()

40

I 0185 0126 0198 4819II 0243 0209 0217 5275III 0239 0332 0230 5646IV 0219 0371 0244 5590V 0241 0459 0238 5153VI 0288 0464 0266 5667VII 0265 0368 0333 6277VIII 0245 0238 0229 5711

60

I 0276 0200 0211 4999II 0279 0286 0262 5591III 0281 0391 0250 6033IV 0267 0469 0139 5477V 0261 0538 0254 5063VI 0337 0554 0290 5870VII 0333 0462 0317 5948VIII 0261 0319 0234 5877

80

I 0437 0308 0245 5068II 0402 0393 0237 5174III 0461 0511 0283 5424IV 0424 0572 0221 5195V 0429 0680 0211 4844VI 0544 0673 0230 5788VII 0547 0573 0284 5724VIII 0483 0380 0219 5654

100

I 0531 0344 0144 4587II 0546 0430 0190 4825III 0573 0554 0133 5156IV 0577 0621 0138 4957V 0673 0746 0143 4800VI 0691 0722 0128 5375VII 0596 0591 0162 5440VIII 0487 0427 0148 5374

Complexity 7

+e coal loading performance of the drum depends onthe axial velocity of particles to a large extent +rough theanalysis of Table 3 and Figure 8 the axial velocity of particlesand the coal loading rate of the drum increase with theincrease in the value of Ψ but when Ψgt100deg with the in-crease in the value of Ψ the axial velocity of particles stillincreases while the coal loading rate decreases +e reasonfor that is the average diameter of the hub was too large dueto the excessive cone angle and the particles in the drumwere compressed by the hub and fell into area II in the formof extrusion Additionally the axial velocity of particles indrums (VI) (VII) and (VIII) was close to that of drums (V)(IV) and (II) respectively However the diameter of thecurve-shaped hub is smaller than that of the conical hub so

the squeezing effect of the particles by the hub was smallerwhich led to a higher coal loading rate

42 e Influence of the Drum Space Capacity on the CoalConveying Performance +e drum space capacity dependson the diameter of the vane and the hub +e cone angle ofthe hub has a negative impact on the drum space capacityespecially in the case of the lower rotational speed and thecoal cutting rate of the drum is bigger than the conveyingflow rate which is prone to clogging +e theoretical con-veying flow of the drum depends on the axial velocity ofparticles and the swept area by vanes which is expressed byequation (6) +e cutting rate of the drum is determined by

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

00

01

02

03

04

05

06M

ean

velo

city

of p

artic

les (

ms

)

48

51

54

57

60

63

Coa

l loa

ding

rate

()

IIIII IV V VII VIIIVIIDrum

(a)

00

01

02

03

04

05

06

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

48

51

54

57

60

Coa

l loa

ding

rate

()

(b)

48

51

54

57

60

Coa

l loa

ding

rate

()

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

(c)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08M

ean

velo

city

of p

artic

les (

ms

)

45

48

51

54

57

Coa

l loa

ding

rate

()

(d)

Figure 8+e relationship between particle velocity in three directions and loading rate at different rotational speeds (a) 40 rpm (b) 60 rpm(c) 80 rpm and (d) 100 rpm

8 Complexity

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 7: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

drum the particle velocity in directions Y and Z increasedwith the increase of the rotational speed while the velocityin the X direction decreased +is is because with theincrease of the rotational speed the action of the vaneswas more obvious and the number and amplitude of thethrown particles increased correspondingly which led to

the increase of the particle velocity in Y and Z directions toan extent Due to the influence of the vanes more particleswere thrown from the right half of the drum to the lefthalf and the movement direction was reversed in the Xdirection resulting in a decrease in the velocity in the Xdirection to some extent

60 80 10040Rotational speed (rpm)

45

50

55

60

65

Coa

l loa

ding

rate

()

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Figure 7 +e coal loading rate curve of eight drums at different rotational speeds

Table 3 +e statistical analysis of particle velocities in three directions and coal loading rate

n (rpm) Drum X direction (ms) Y direction (ms) Z direction (ms) Loading rate ()

40

I 0185 0126 0198 4819II 0243 0209 0217 5275III 0239 0332 0230 5646IV 0219 0371 0244 5590V 0241 0459 0238 5153VI 0288 0464 0266 5667VII 0265 0368 0333 6277VIII 0245 0238 0229 5711

60

I 0276 0200 0211 4999II 0279 0286 0262 5591III 0281 0391 0250 6033IV 0267 0469 0139 5477V 0261 0538 0254 5063VI 0337 0554 0290 5870VII 0333 0462 0317 5948VIII 0261 0319 0234 5877

80

I 0437 0308 0245 5068II 0402 0393 0237 5174III 0461 0511 0283 5424IV 0424 0572 0221 5195V 0429 0680 0211 4844VI 0544 0673 0230 5788VII 0547 0573 0284 5724VIII 0483 0380 0219 5654

100

I 0531 0344 0144 4587II 0546 0430 0190 4825III 0573 0554 0133 5156IV 0577 0621 0138 4957V 0673 0746 0143 4800VI 0691 0722 0128 5375VII 0596 0591 0162 5440VIII 0487 0427 0148 5374

Complexity 7

+e coal loading performance of the drum depends onthe axial velocity of particles to a large extent +rough theanalysis of Table 3 and Figure 8 the axial velocity of particlesand the coal loading rate of the drum increase with theincrease in the value of Ψ but when Ψgt100deg with the in-crease in the value of Ψ the axial velocity of particles stillincreases while the coal loading rate decreases +e reasonfor that is the average diameter of the hub was too large dueto the excessive cone angle and the particles in the drumwere compressed by the hub and fell into area II in the formof extrusion Additionally the axial velocity of particles indrums (VI) (VII) and (VIII) was close to that of drums (V)(IV) and (II) respectively However the diameter of thecurve-shaped hub is smaller than that of the conical hub so

the squeezing effect of the particles by the hub was smallerwhich led to a higher coal loading rate

42 e Influence of the Drum Space Capacity on the CoalConveying Performance +e drum space capacity dependson the diameter of the vane and the hub +e cone angle ofthe hub has a negative impact on the drum space capacityespecially in the case of the lower rotational speed and thecoal cutting rate of the drum is bigger than the conveyingflow rate which is prone to clogging +e theoretical con-veying flow of the drum depends on the axial velocity ofparticles and the swept area by vanes which is expressed byequation (6) +e cutting rate of the drum is determined by

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

00

01

02

03

04

05

06M

ean

velo

city

of p

artic

les (

ms

)

48

51

54

57

60

63

Coa

l loa

ding

rate

()

IIIII IV V VII VIIIVIIDrum

(a)

00

01

02

03

04

05

06

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

48

51

54

57

60

Coa

l loa

ding

rate

()

(b)

48

51

54

57

60

Coa

l loa

ding

rate

()

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

(c)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08M

ean

velo

city

of p

artic

les (

ms

)

45

48

51

54

57

Coa

l loa

ding

rate

()

(d)

Figure 8+e relationship between particle velocity in three directions and loading rate at different rotational speeds (a) 40 rpm (b) 60 rpm(c) 80 rpm and (d) 100 rpm

8 Complexity

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 8: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

+e coal loading performance of the drum depends onthe axial velocity of particles to a large extent +rough theanalysis of Table 3 and Figure 8 the axial velocity of particlesand the coal loading rate of the drum increase with theincrease in the value of Ψ but when Ψgt100deg with the in-crease in the value of Ψ the axial velocity of particles stillincreases while the coal loading rate decreases +e reasonfor that is the average diameter of the hub was too large dueto the excessive cone angle and the particles in the drumwere compressed by the hub and fell into area II in the formof extrusion Additionally the axial velocity of particles indrums (VI) (VII) and (VIII) was close to that of drums (V)(IV) and (II) respectively However the diameter of thecurve-shaped hub is smaller than that of the conical hub so

the squeezing effect of the particles by the hub was smallerwhich led to a higher coal loading rate

42 e Influence of the Drum Space Capacity on the CoalConveying Performance +e drum space capacity dependson the diameter of the vane and the hub +e cone angle ofthe hub has a negative impact on the drum space capacityespecially in the case of the lower rotational speed and thecoal cutting rate of the drum is bigger than the conveyingflow rate which is prone to clogging +e theoretical con-veying flow of the drum depends on the axial velocity ofparticles and the swept area by vanes which is expressed byequation (6) +e cutting rate of the drum is determined by

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

00

01

02

03

04

05

06M

ean

velo

city

of p

artic

les (

ms

)

48

51

54

57

60

63

Coa

l loa

ding

rate

()

IIIII IV V VII VIIIVIIDrum

(a)

00

01

02

03

04

05

06

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

48

51

54

57

60

Coa

l loa

ding

rate

()

(b)

48

51

54

57

60

Coa

l loa

ding

rate

()

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08

Mea

n ve

loci

ty o

f par

ticle

s (m

s)

(c)

Mean velocity inX directionMean velocity inY direction

Mean velocity inZ directionCoal loading rate

IIIII IV V VII VIIIVIIDrum

00

01

02

03

04

05

06

07

08M

ean

velo

city

of p

artic

les (

ms

)

45

48

51

54

57

Coa

l loa

ding

rate

()

(d)

Figure 8+e relationship between particle velocity in three directions and loading rate at different rotational speeds (a) 40 rpm (b) 60 rpm(c) 80 rpm and (d) 100 rpm

8 Complexity

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 9: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

the diameter hauling speed and web depth of the drumwhich represents the volume of the coal excavated in unittime and is expressed by equation (7) +e theoretical axialvelocity of particles cutting rate of the drum and drumspace capacity were studied by Gao et al [31] in detail

Qz Qv middot Vp (6)

where Qz is the conveying flow rate of the drum Qv is theswept area by the loading vane and Vp is the axial velocity ofcoal particles

Qt 2J middot Rc middot Vq middot Ψv (7)

whereQt is the cutting rate of the drum J is the web depth Rcis the radius of the drum Vq is the hauling speed of thedrum and ψv is the loose coefficient of the coal

In the simulation the volume of excavated particles doesnot change after being cut off from the coal face so the loosecoefficient in the simulation was not taken into accountAdditionally there will be voids between particles in the coalface during the stacking process so equation (7) wasamended to the following equation

Qt 2J middot Rc middot Vq middot 1 minus Ψq1113872 1113873 (8)

where ψq is the porosity of the particlesTable 4 and Figure 9 show the difference between the

drum conveying flow rate and cutting rate at different drumrotational speeds

In the case of different rotational speeds the relationshipbetween the conveying flow rate of the drum and the coalloading rate is shown in Figure 9 In can be seen that fromFigure 9(a) the smaller the difference between conveyingflow rate and coal cutting rate is the higher loading rate ofthe drum is this is because the filling rate of particles in theenveloping zone of vanes was large and the action of thevanes and the hub on the particles was obvious whichcaused an increase in the coal loading rate When the coalconveying flow rate of the drum was far bigger than thecutting rate as drums (I) and (II) the filling rate of particleswas too small and effect of vanes and the hub on particleswas weak Moreover as the value of Ψ is increased theaverage diameter of the hub increases which caused thesmaller depth of vanes and smaller drum space capacitywhich increase the probability of particles accumulated inthe left half of the drum and being thrown into the goaf asshown in Figure 10

As the rotational speed increases in Figure 9 from 9(b)to 9(d) it can be seen that although the conveying flowdifference was the smallest the coal loading rate was not thehighest which proved that with the increase in rotation theinfluence degree of the drum space capacity on the coalloading performance gradually decreased

Figure 11 shows the contact forces between particles indifferent zones As the rotational speed increases the drumconveying performance increases the packing density ofparticles in the drum was small and the contact betweenparticles was not intimate so the contact forces in thestatistical area decreased By analyzing the difference incontact force between areas 1 and 2 it can be seen that the

contact force in area 2 was significantly greater than that inarea 1 at a lower rotational speed As the rotational speedincreases the difference in contact force decreases when therotational speed reached 100 rpm the particle contact forcein area 1 was slightly bigger than that in area 2 +e mainreason for that is when the rotational speed was low theparticles obtained a smaller ejection velocity With the helpof the gravity a large amount of particles accumulated inarea 2 and the number of particles in area 1 was lessresulting in the contact force far less than that in area 2More particles were thrown to area 1 with the increase of therotational speed which led to the decrease of contact forceWhen the rotational speed reached 100 rpm the particlecontact in area 1 would be more than that in area 2 so thecontact force was slightly greater than that in area 2 It can beseen from Figure 11 that from statistical zone A to E thecontact force increased first and then decreased and reachedthe maximum value in zone C Because under the action ofvanes the particles were conveyed to the chain conveyorfrom the larger web depth more particles were piled up inzone C which led to the increase in contact force and zoneD and E were close to the chain conveyor where the particleswere relatively scattered so the contact forces were smallMeanwhile with the increase of rotational speed the fluc-tuation range of particle contact force decreases In com-parison with Table 4 and Figure 11 the particle contact forcewas negatively related to the drum space capacity When theconveying flow rate was less than the coal cutting rate of thedrum the particle contact force was a peak value +ereforefrom the perspective of the drum space capacity the value ofΨ should be in a reasonable range

43e Effect of the Drum Rotational Speed and Structures ofthe Drum Hub on the Number of Coal Particles in the DrumFigure 12 shows the cumulative mass of particles passingthrough statistical zones A B C D and E in areas 1 and 2respectively according to different web depths It can be seenfrom the figure that the particles move axially towards thechain conveyor under the action of vanes and sequentiallypass through statistical zones A B C D and E so the cu-mulative mass of the particles increases gradually fromA to E

Figure 12 indicates that the cumulative mass growth rateof particles in the drum decreases as the rotational speedincreases and the mass of particles left in area E at 40 rpmwas about twice that at 100 rpm which proved that lowrotational speed was favorable for particles to remain in thedrum and reduced the probability of particles becomingfloating coal Meanwhile the particle cumulative mass in theconical hub drum was obviously smaller than that in thecylinder hub drum as the cone angle of the hub had anadverse effect on the drum space capacity Compared withTable 3 and Figure 12 the larger the cumulative mass ofparticles in both zone 1 and area E was the higher theloading rate was +e reason for that was the altitude of zone1 was greater than that of area 2 and the particles in zone 1were easier to complete the effective loading with ejectionAs the particles in area 2 were squeezed by the hub they wereinclined to fall into statistical area II

Complexity 9

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 10: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

As shown in Figures 12(f )ndash12(h) the change law of thecoal loading rate of drum (VII) was consistent with thechange law of particle cumulative mass while the coalloading rate of drums (VI) and (VIII) increases first and thendecreases as the rotational speed increases which was notconsistent with the change law of particle cumulative mass+e main reason was that the value of K3 of drums (VI) and(VIII) was 0 the structure of the drum hub was cylinderwhile the structure of drum (VII) was still curve-shapedwhich proved that the curve-shaped hub was more favorable

to the axial movement of particles Meanwhile the coalloading rate of drum (VII) was generally higher than that ofdrums (VI) and (VIII) especially in the case of low rota-tional speed which indicated that the hub with a smallchange of value of K should be used in the conditions of lowrotational speed

By analyzing the relationship between coal loading rateand cumulative mass of particles in the conical hub drum andcurve-shaped hub drum respectively it was found that thecumulative mass and the loading rate of the curve-shaped hub

Table 4 +e difference between conveying flow rate and cutting rate of drums with different rotational speeds

n (rpm) Qt (m3min) 1371Drum I II III IV V VI VII VIII

40 Qz (m3min) 1911 1675 1402 1085 0715 1319 1368 1652Qz minusQt (m3min) 0540 0304 0031 minus0286 minus0656 minus0052 minus0003 0281

60 Qz (m3min) 2867 2513 2103 1628 1073 1979 2052 2478Qz minusQt (m3min) 1496 1142 0732 0257 minus0298 0608 0681 1107

80 Qz (m3min) 3822 3350 2804 2170 1430 2638 2736 3304Qz minusQt (m3min) 2451 1979 1433 0799 0059 1267 1365 1933

100 Qz (m3min) 4778 4188 3505 2713 1788 3298 3420 4130Qz minusQt (m3min) 3407 2747 2134 1342 0417 1919 2049 2759

08

06

04

02

00

ndash02

ndash04

ndash06

ndash08

ndash10

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

24

20

16

12

08

04

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(a)

20

16

04

08

12

00

ndash04

ndash08

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

32

28

24

20

16

12

08

1371

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(b)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

32

28

24

20

16

12

08

04

00

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(c)

Con

veyi

ng fl

ow d

iffer

ence

(m3 m

in)

Con

veyi

ng fl

ow (m

3 min

)

60

50

40

30

20

10

0

Coa

l loa

ding

rate

()

1371

42

36

30

24

18

12

06

00

52

48

44

40

36

32

28

24

20

16

12

The line of loading rateThe line of conveying flowConveying flow difference

IIIII IV V VII VIIIVIIDrum

(d)

Figure 9 +e relationship between the coal loading rate and coal conveying flow (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

10 Complexity

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 11: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

Vane edge

Pick

Cylinderhub

n1

2

Coal face

(a)

Vane edge

Pick

Cylinderhub

n

1

2

Coal face

Conicalhub

(b)

Figure 10 Schematic diagram of the influence of the drum space capacity on the coal conveying performance (a) the coal conveying processwith the cylinder hub drum (b) the coal conveying process with the conical hub drum

C D EBA

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

0

25

50

75

100

125

150

175

200

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

B C D EA

Statistical zone 1

(a)

5040302010

0

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

050

100150200250300350400450

B C D EA

(b)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

0

5

10

15

20

25

30

35

(c)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

05

101520253035404550

(d)

Figure 11 Continued

Complexity 11

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 12: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

drum were both greater than those of the conical hub drumwhich proved that the curve-shaped hub drum can provide abetter drum space capacity and conveying performance

Figure 13 shows the particle cumulative mass in differentstatistical areas of four drums ((I) (III) (V) and (VI)) changingwith time It can be seen from the figure that the particlecumulative mass in the area was linearly related to the time asthe coal cutoff by the drum was a continuous processMeanwhile the particles move axially under the action of vanesthrough the statistical areas from zoneA to E in turn+ereforein an ideal situation the particle cumulative mass from zone Bto E should be two to five times of that in zone A respectivelyIn Figure 13 the slope of the fitting line of the particle cu-mulative mass should also increase linearly correspondinglyWhile the actual situation was that the difference of slopeincreases first and then decreases from zone A to E as shown inTable 5+emain reason was that the movement of particles inthe axial direction was fluent and with the continuous ac-cumulation of particles in the drum more and more particleswere thrown into the goaf resulting in the decrease of slope

difference Additionally due to the large drum space capacityof drum (I) and the large number of particles in the drum theslope of the fitting line was larger than that of other drums Itcan also be seen that compared with drums (I) and (III) thedifference of the cumulative curve slope between statisticalzones A and B and areas B and C in drum (I) was slightlybigger than that in drum (III) but the difference of thecumulative curve slope between statistical zones C and D andareas D and E in drum (I) was smaller than that in drum (III)which proved that the particle conveying performance of thecylinder hub was worse than that of the conical hub whichwas consistent with the change law between the loading rateand particle cumulative mass Due to the limitation of thedrum space capacity the slope difference of particle cumu-lative mass in different statistical areas of drums (V) and (VI)was smaller than that of the above two drums

44 e Effect of the Drum Hub on the Loading Rate of CoalParticles in Different Web Depths Figure 14 shows the

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

150

(e)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

25

50

75

100

125

(f)

C D EBAStatistical zone 1

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(g)

C D EBAStatistical zone 2

Drum IDrum IIDrum IIIDrum IV

Drum VDrum VIDrum VIIDrum VIII

Part

icle

s con

tact

forc

es (N

)

00

15

30

45

60

75

90

(h)

Figure 11 +e contact force between particles in different statistical areas with different rotational speeds

12 Complexity

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 13: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

Tota

l mas

s (kg

)

51015202530

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(a)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(b)

5

10

15

20

25

Mas

s in

area

1 (k

g)To

tal m

ass (

kg)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(c)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(d)

Tota

l mas

s (kg

)

5

0

10

15

20

Mas

s in

area

1 (k

g)

05

1015202530

Mas

s in

area

2 (k

g)

01020304050

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(e)

Tota

l mas

s (kg

)

5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(f )

Figure 12 Continued

Complexity 13

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 14: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

yA = 1499x + 0106 R2 = 0997yB = 3801x ndash 0081 R2 = 0999yC = 3625x ndash 0716 R2 = 0999yD = 8781x ndash 1715 R2 = 0999yE = 10695x ndash 2617 R2 = 0998

1 62 5430Simulation time (s)

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(a)

yA = 1191x ndash 0076 R2 = 0996yB = 3403x ndash 0397 R2 = 0999yC = 5906x ndash 1066 R2 = 0999yD = 8376x ndash 1745 R2 = 0999yE = 10373x ndash 2518 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(b)

Figure 13 Continued

Tota

l mas

s (kg

)5

0

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

0102030405060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(g)

Tota

l mas

s (kg

)

5

10

15

20

25

Mas

s in

area

1 (k

g)

0

10

20

30

40

Mas

s in

area

2 (k

g)

01020304050

7060

B DA ECStatistical area in different web depths

40rpm60rpm

80rpm100rpm

(h)

Figure 12 Cumulative mass of coal particles in different statistical areas (a) drum I (b) drum II (c) drum III (d) drum IV (e) drum V (f )drum VI (g) drum VII and (h) drum VIII

14 Complexity

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 15: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

yA = 0413x + 0033 R2 = 0997yB = 1856x ndash 0073 R2 = 0997yC = 3870x ndash 0350 R2 = 0997yD = 5691x ndash 0864 R2 = 0997yE = 7540x ndash 1358 R2 = 0998

0

10

20

30

40

50

60

70Ac

cum

ulat

ed m

ass o

f par

ticle

sin

stat

istic

al zo

ne (k

g)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(c)

yA = 1278x + 0064 R2 = 0998yB = 3509x ndash 0068 R2 = 0999yC = 5913x ndash 0759 R2 = 0999yD = 8132x ndash 1542 R2 = 0999yE = 9743x ndash 2227 R2 = 0998

0

10

20

30

40

50

60

70

Accu

mul

ated

mas

s of p

artic

les

in st

atist

ical

zone

(kg)

1 62 5430Simulation time (s)

Statistical zone AStatistical zone BStatistical zone C

Statistical zone DStatistical zone EThe fit line

(d)

Figure 13 Cumulative mass of coal particles in different statistical areas changes with time at 60 rpm (a) drum I (b) drum III (c) drum Vand (d) drum VI

Table 5 +e difference of the slope of the cumulative coal particle mass curve in different statistical areas

+e difference in the slope of the fitting lineDrum yB minus yA yC minus yB yD minus yC yE minus yDI 2302 2524 2456 1914III 2212 2503 2470 1997V 1443 2014 2091 1580VI 2231 2404 2219 1611

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

48195275

5646 55905153

56676277

5711

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(a)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

49995591

60335477

5063

5870 5948 5877

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

(b)

Figure 14 Continued

Complexity 15

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 16: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

5068 5174 5424 51954844

5788 5724 5654

0

10

20

30

40

50

60

70

Coa

l loa

ding

rate

()

0

5

10

15

20

25Pe

rcen

tage

of d

iffer

ent p

artic

les (

)

(c)

Yellow particlesBlue particlesRed particles

Green particlesOrange particlesCoal loading rate

I II III IV V VI VII VIIIDrum

45874825

5156 4957 48005375 5440 5374

0

10

20

30

40

50

60

Coa

l loa

ding

rate

()

0

5

10

15

20

25

Perc

enta

ge o

f diff

eren

t par

ticle

s (

)

(d)

Figure 14 +e relationship between the loading coal particles with different web depths at different rotational speeds and the coal loadingrate of the drum (a) 40 rpm (b) 60 rpm (c) 80 rpm and (d) 100 rpm

Table 6 +e statistical results of coal particle mass in different areas

n (rpm) Drum Area I (kg) Area II (kg) Area III (kg) Loading rate () E ()

40

I 4180 2164 5902 4819 1767II 3762 2024 6460 5275 1653III 3549 1782 6915 5646 1455IV 3493 1907 6846 5590 1557V 3862 2073 6311 5153 1693VI 3527 1778 6941 5667 1452VII 2817 1741 7688 6277 1422VIII 3472 1780 6994 5711 1454

60

I 4222 1902 6122 4999 1553II 3583 1816 6847 5591 1483III 3230 1627 7389 6033 1329IV 3729 1809 6708 5477 1477V 3989 2056 6201 5063 1679VI 3382 1675 7189 5870 1368VII 3246 1715 7285 5948 1400VIII 3368 1681 7197 5877 1373

80

I 4378 1661 6207 5068 1356II 4367 1542 6337 5174 1259III 4014 1589 6643 5424 1298IV 4301 1583 6362 5195 1293V 4669 1654 5933 4844 1350VI 3654 1503 7089 5788 1227VII 3790 1446 7010 5724 1181VIII 3865 1457 6924 5654 1190

100

I 5550 1079 5617 4587 881II 4934 1403 5909 4825 1146III 4701 1230 6315 5156 1004IV 4885 1290 6071 4957 1053V 5175 1192 5879 4800 973VI 4357 1306 6583 5375 1066VII 4308 1275 6663 5440 1041VIII 4395 1270 6581 5374 1037

16 Complexity

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 17: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

percentage of particles with different colors (representingdifferent web depth positions) in the coal loading rate Asshown in the figure the proportion of yellow particles in areaIII is the largest followed by blue red green and orangeparticles which was exactly the same with the web depth ofparticles with different colors +e proportion of yellow andred particles near the chain conveyor was relatively largewhile that of orange and green particles was relatively smalldue to the larger web depth Meanwhile the change law ofthe drum loading rate was similar to the proportion trend ofparticles in colors of blue red and green indicating that thecoal particles in these colors mainly affected the coal loadingperformance of the drum With the increase of rotatingspeed the proportion of yellow and blue particles did notchange significantly while the proportion of red particlesand green particles had a significant reduction which provedthat the particles near the chain conveyor were less affectedby the drum rotating speed and the high rotational speedhad a negative impact on the conveying of particles withlarger web depth

Table 6 is the statistics of particle mass in each statisticalarea where E is the ratio of particle mass in statistical area IIto the total mass of cutoff particles It can be seen from thetable that there was a negative correlation between the valueof E and the drum loading rate Meanwhile due to theinfluence of the particle axial velocity the value of E de-creases with the increase in the value of ψ When ψ gt 100degthe value of E increases with the increase in the value of ψdue to the influence of the hub extrusion which was es-pecially obvious at a low rotational speed

Figure 15 shows the loading process of the drum in thesimulation when the rotational speed was 40 rpm Under the

action of vanes the excavated particles were conveyed fromthe coal wall to the chain conveyor and some of them werepiled up in area II which failed to load onto the conveyorWith the continuous mining the particles were accumulatedin area II continuously and the particles were stacked in thechute of the conveyor in a wedge shape For the measure-ment of the stacking angle θ of particles the value of θ wasthe angle between the bevel edge and the bottom edge +elarger the value of θ was the more particles were piled up inarea II which will become an obstacle for the subsequentparticles to be thrown out from the drum and affect themovement of the chain conveyor towards to the coal face Byanalyzing Figure 14 and Table 6 the larger stacking anglewas adverse on the drum loading performance

5 Conclusion

Seven drums with different hub forms and structures weredesigned and developed based on the cylindrical hub drumDEM was employed in this paper to study the loadingperformance of the drums above with different rotationalspeeds +e complex influence mechanism of the drum hubon the coal loading performance was analyzed and studiedby some research objects including the particle velocitydrum space capacity and contact force between particles+e main conclusions are as follows

(1) By analyzing the axial velocity variation of coalparticles with different drum hubs from the simu-lation it was found that the axial velocity of particlesincreases with the increase of hub cone angle fur-thermore the axial velocity difference on the lower

Coal face Drum I

Area I Area II Area III

θ = 2397deg

θ

(a)

Coal face Drum II

Area I Area II Area III

θ = 2175deg

θ

(b)

Coal face Drum III

Area I Area II Area III

θ = 2096deg

θ

(c)

Coal face Drum IV

Area I Area II Area III

θ = 2208deg

θ

(d)

Coal face Drum V

Area I Area II Area III

θ = 2289deg

θ

(e)

Coal face Drum VII

Area I Area II Area III

θ = 2058deg

θ

(f )

Figure 15 Simulation results in the DEM at rotational speed 40 rpm

Complexity 17

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 18: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

rotational speed was obviously greater than that onthe higher rotational speed When the rotationalspeed of the drum increased from 40 rpm to 100 rpmthe axial velocity difference of particles in the drumwith a cone angle of 110degand in the cylindrical hubdrum decreased from 4 times to 2 times

(2) +e increased hub cone angle had a positive effect onincreasing axial velocity of particles and the loadingrate of particles at larger web depth nevertheless ithad a negative effect on drum space capacity +esmaller drum space capacity would lead to drumchoking and further lead to the bigger contact forcebetween particles overcrushing and particle sizereduction during the conveying process+rough theDEM simulation the drum had a best coal loadingperformance with the cone angle 100deg and the ro-tational speed 60 rpm and the coal loading rate was6033 which is about 10 higher than that of thecylindrical hub drum

(3) Based on the conical hub drum three drums with thecurve-shaped hub were established Compared withthe conical hub drum the curve-shaped hub drumnot only increased the axial velocity of particles butalso provided the bigger drum space capacity Underthe same rotational speed the loading performanceof the drum with the curve-shaped hub was betterthan that with the conical hub drum +rough thesimulation the best loading rate was obtained at40 rpm by the drum whose curvature changed from01224 007984 and 002735 along the end plate tothe discharge end and the coal loading rate was6277

Data Availability

+e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

+e authors declare that they have no conflicts of interest

Acknowledgments

+is work was supported by the National Natural ScienceFoundation of China (51704178) the Natural ScienceFoundation of Shandong Province (ZR2017MEE034) theOpen Foundation of Shandong Province Key Laboratory ofMine Mechanical Engineering (2019KLMM102) and theProject of Shandong Province Higher Educational YoungInnovative Talent Introduction and Cultivation Team(Performance enhancement of deep coal miningequipment)

References

[1] O Z Hekimoglu and L Ozdemir ldquoEffect of angle of wrap oncutting performance of drum shearers and continuousminersrdquoMining Technology vol 113 no 2 pp 118ndash122 2004

[2] B Mishra Analysis of Cutting Parameters and Heat Gener-ation on Bits of a Continuous Miner-Using Numerical andExperimental Approach College of Engineering and MineralResources at West Virginia University Morgantown WVUSA 2007

[3] D Yang J Li L Wang K Gao Y Tang and Y WangldquoExperimental and theoretical design for decreasing wear inconical picks in rotation-drilling cutting processrdquo e In-ternational Journal of Advanced Manufacturing Technologyvol 77 no 9ndash12 pp 1571ndash1579 2015

[4] L Zhao H Liu and W Zhou ldquoA study on the dynamictransmission law of spiral drum cutting coal rock based onANSYSLS-DYNA simulationrdquo Complexity vol 2019 ArticleID 1482051 14 pages 2019

[5] S-F Liu S-F Lu Z-J Wan H-W Zhang and K-K XingldquoNumerical simulation of induced cutting in deep coalrdquo RoyalSociety Open Science vol 6 no 9 Article ID 190308 2019

[6] J Huang Y Zhang L Zhu and T Wang ldquoNumericalsimulation of rock cutting in deep mining conditionsrdquo In-ternational Journal of Rock Mechanics and Mining Sciencesvol 84 pp 80ndash86 2016

[7] CM Booker ldquo+eoretical and practical aspects of cutting andloading by shearer drumsrdquo Colliery Guardian vol 1 pp 9ndash161979

[8] J Ludlow and R A Jankowski ldquoUse low shearer drum speedsto achieve deeper coal cuttingrdquo Mining Engineering vol 36pp 251ndash255 1984

[9] S S Peng Longwall Mining United States West VirginiaUniversity Department of Mining Engineering Morgan-town WV USA 2006

[10] K G Hurt and F G Mcstravick ldquoHigh performance shearerdrum designrdquo Colliery Guardian vol 236 pp 425ndash429 1988

[11] M Ayhan and E M Eyyuboglu ldquoComparison of globoid andcylindrical shearer drumsrsquo loading performancerdquo Journal ofthe South Africa Institute of Mining and Metallurgy vol 106no 1 pp 55-56 2006

[12] S Liu C Du J Zhang and H Jiang ldquoParameters analysis ofshearer drum loading performancerdquo Mining Science andTechnology (China) vol 21 no 5 pp 621ndash624 2011

[13] K Gao C Du J Dong and Q Zeng ldquoInfluence of the drumposition parameters and the ranging arm thickness on the coalloading performancerdquoMinerals vol 5 no 4 pp 723ndash736 2015

[14] Ł Bołoz ldquoUnique project of single-cutting head longwallshearer used for thin coal seams exploitationrdquo Archives ofMining Sciences vol 58 no 4 pp 1057ndash1070 2013

[15] T Wydro ldquoInfluence of the plow filling and thread angle ontothe plow head efficiencyrdquo Archives of Mining Sciences vol 60no 1 pp 143ndash156 2015

[16] P Gospodarczyk ldquoModeling and simulation of coal loadingby cutting drum in flat seamsrdquo Archives of Mining Sciencesvol 61 no 2 pp 365ndash379 2016

[17] P A Cundall ldquoComputer model for simulating progressivelarge scale movements in blocky rock systemsrdquo in Proceedingsof the Symposium of the International Society of Rock Me-chanics vol 1 no 2 Nancy France 1971

[18] P A Cundall and O D L Strack ldquoA discrete numericalmodel for granular assembliesrdquo Geotechnique vol 29 no 1pp 47ndash65 1979

[19] X Deng K Zheng and R N Dave ldquoDiscrete element methodbased analysis of mixing and collision dynamics in adhesivemixing processrdquo Chemical Engineering Science vol 190pp 220ndash231 2018

[20] C Hang Y Huang and R Zhu ldquoAnalysis of the movementbehaviour of soil between subsoilers based on the discrete

18 Complexity

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19

Page 19: ComplexEffectsofDrumHubFormsandStructural ...downloads.hindawi.com/journals/complexity/2020/7036087.pdf · curve-shaped hub drum can not only improve the coal loading rate, but also

element methodrdquo Journal of Terramechanics vol 74pp 35ndash43 2017

[21] S T W Karuneru E Sauret S C Saha and Y T Gu ldquoAcoupled finite volume amp discrete element method to examineparticulate foulant transport in metal foam heat exchangersrdquoInternational Journal of Heat and Mass Transfer vol 115pp 43ndash61 2017

[22] S Shrestha S B Kuang A B Yu and Z Y Zhou ldquoEffect ofvan derWaals force on bubble dynamics in bubbling fluidizedbeds of ellipsoidal particlesrdquo Chemical Engineering Sciencevol 212 Article ID 115343 2020

[23] M D Sinnott and PW Cleary ldquoParticulate and water mixingin the feed box for a screenrdquo Minerals Engineering vol 109pp 109ndash125 2017

[24] X Wang B Li S Wang Z Yang and L Cai ldquo+e trans-porting efficiency and mechanical behavior analysis of scraperconveyorrdquo Proceedings of the Institution of Mechanical En-gineers Part C Journal of Mechanical Engineering Sciencevol 232 no 18 pp 3315ndash3324 2018

[25] D Ilic and C A Wheeler ldquoTransverse bulk solid behaviourduring discharge from troughed belt conveyorsrdquo AdvancedPowder Technology vol 28 no 9 pp 2410ndash2430 2017

[26] D O Potyondy and P A Cundall ldquoA bonded-particle modelfor rockrdquo International Journal of RockMechanics andMiningSciences vol 41 no 8 pp 1329ndash1364 2004

[27] Y Dai F Ma X Zhu H Liu Z Huang and Y Xie ldquoMe-chanical tests and numerical simulations for mining seafloormassive sulfidesrdquo Journal of Marine Science and Engineeringvol 7 no 8 p 252 2019

[28] X Li SWang S Ge R Malekian Z Li and Y Li ldquoA study ondrum cutting properties with full-scale experiments andnumerical simulationsrdquo Measurement vol 114 pp 25ndash362018

[29] K D Gao ldquoFeasibility of drum coal loading process simu-lation using three dimension discrete element methodrdquoElectronic Journal of Geotechnical Engineering vol 20pp 5999ndash6007 2015

[30] M Ayhan Investigation into the Cutting and Loading Per-formance of Drum Shearers in OAL Mine +e University ofHacettepe Ankara Turkey 1994

[31] K D Gao X Zhang K Jiang et al ldquoAn applied model ofminimum rotating speed for drum shearer to avoid drumcloggingrdquo Journal of Engineering vol 7 no 1 pp 1ndash19 2019

Complexity 19