Y.R. Goh; C.N. Lim; R. Zakaria; K.H. Chan; G. Reynolds; Y.B. Yan -- Mixing, Modelling and Measurement

7/23/2019 Y.R. Goh; C.N. Lim; R. Zakaria; K.H. Chan; G. Reynolds; Y.B. Yan -- Mixing, Modelling and Measurement

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MIXING, MODELLING AND MEASUREMENTS OF

INCINERATOR BED COMBUSTION

Y. R. GOH (ASSOCIATE MEMBER), C. N. LIM (ASSOCIATE MEMBER), R. ZAKARIA, K. H. CHAN (ASSOCIATE MEMBER),G. REYNOLDS (ASSOCIATE MEMBER), Y. B. YANG, R. G. SIDDALL, V. NASSERZADEH ( ASSOCIATE MEMBER) and

J. SWITHENBANK (FELLOW)

Shefeld University W aste Incineration Centre (SUWIC), Department of Chemical and Process Engineering, University of Shefeld, Shefeld, UK

The safe disposal of municipal solid waste has now become an urgent environmentalproblem. The traditional method of landlling waste has created so manyenvironmental problems that countries including Denmark, Holland and Germany

have imposed severe restrictions on landlling burnable waste. With up to 1 tonne of municipalwaste being generated by every individual annually in the UK, incineration is now at theforefront of combustion research, as developed countries recognize the environmentally

friendly advantages of this technology. An efcient incinerator is not only assessed by theamount of heat recovery but also by the levels of emissions and quality of the ash it produces.Incinerator designs must therefore be fully optimized so that they can control emissions byreducing the production of harmful pollutants such as dioxins, furans, NOx and SOx. Hence,incinerator bed combustion is a vital area that urgently needs further investigation. AtSUWIC, the present work concentrates on the development of a comprehensive and reliablemodel for the incinerator bed combustion process. The results from the incinerator burningbed model can then provide the much needed boundary conditions for ComputationalFluid Dynamics (CFD) modelling of the gas phase reacting turbulent ow in the freeboardregion of an incinerator. In addition to the development of the computational model,the work involves several parallel activities, including experimental investigations intowaste combustion, solid mixing and prevention of slag formation and instrumentationdevelopment.

Keywords: waste incineration; slag formation; instrumentation; mixing; mathematicalmodelling; pollution.

INTRODUCTION

The amount of waste generated by mankind and the growingconcern over health and environmental problems relatedto landll has risen to a point where incineration is per-ceived to be the best option to dispose of most wastes,especially when some of the energy content of the waste can

be recovered. Incineration is an environmentally friendlyprocess for the disposal of municipal solid waste, providedthat it is properly carried out. The main objective ofincineration is to convert a large volume of chemicallyand biologically active waste into a small volume of inertmatter.

In any technology, the design process depends on a clearunderstanding of the fundamental scientic principleson which the design is to be based. These fundamentalprinciples are usually expressed in terms of the governingdifferential equations of the process under consideration.The required design is then obtained by solving these

equations subject to the appropriate boundary conditions,physical constants, input and output conditions. In incin-erators, the main combustion-related design items are theburning bed of solid waste on the grate and the gas phasepath, including the reactions which take place. For the gasphase, advances in CFD have proved to be invaluable

for assessing proposed designs of incinerator, or trouble-shooting existing plant designs, without building the plantor small-scale accurate physical models.

The evolution of better and more efcient incineratorsin the UK is currently hindered by the lack of reliable data,and fundamentally based design procedures to assist theirdesign/manufacture, operation and control. The combus-

tion of waste in incinerators is complex, and the designand control of such processes poses many problems. Forexample, many existing grate systems do not agitate theburning refuse efciently. Consequently, a large volume ofexcess air is required to achieve a good burn-out. This leadsto problems with the gas phase combustion, overloadingof the electrostatic precipitators and/or scrubbers, and highparticulate emissions from the bed. SUWIC studies at someUK municipal incinerators with moving grate systemsalso showed high levels of unburned carbon in the residualand y ash, which increases the cost of ash disposal. Incontrast to the progress in gas phase combustion modelling

with CFD, the open literature contains no satisfactory modelfor the burning of municipal solid waste on a travellinggrate. The prediction of the ow rate and composition ofgases emerging from the bed is particularly important asit provides the upstream boundary conditions for the owcalculation in the gas phase region.

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09575820/00/$10.00+0.00q Institution of Chemical Engineers

Trans IChemE, Vol 78, Part B, January 2000


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MODELLING OF SOLID MIXING ON AMOVING GRATE

A crucial feature of incinerator combustion is the mixingof the solid material on the grate. To achieve complete com-bustion of solid waste in a municipal incinerator, produc-ing as few toxic contaminants as possible, it is essential toacquire experimental information about the combustion

processes on the travelling grate. Existing grate systemsdo not produce a uniform gas concentration distributionabove the burning refuse, and a large volume of excess airis usually required to achieve good ue gas burn-out (typi-cally using 100% excess air). These non-uniformities leadto the aforementioned problems with the gas phase com-bustion, overloading of the ue gas scrubbing system, highparticulate carryover from the bed and high levels ofunburned carbon in both the residual ash and the y ash,which makes it expensive to dispose of the ash.

In this part of the study, the mixing process on scalemodels of three industrial grates has been quantitativelydetermined by a series of systematic particle movement

experiments (random lateral and vertical motion). For eachconguration, sufcient data have been collected to permit anew mathematical model for the mixing process statisticsto be developed. To characterize and quantify the mixingprocess, experiments were conducted in the followingsmall-scale industrial grates (1:15 size ratio): (i) DeutscheBabcock grate (as shown in Figure 1); (ii) Martin grate(Figure 2); and (iii) ABB double motion overthrusthorizontal grate (Figure 3).

Mixing is essentially the dispersion of material from aninitial position, so to quantify this, it is necessary to seewhere material can progress to, once it has left the initial

position. In the experiments, a xed volume of solids wasintroduced onto the grate contained in a perspex box, asshown in Figure 1. Marked or coloured solid tracers werepositioned on the original bed of solids. A digital imagevideo camera was then used to record the movements of thetracers. Digital frames of the test were captured at vesecond intervals. The position of each tracer on each framewas evaluated in terms of (x,y) and time, where x is thedistance measured from the point of refuse input, and y isthe distance measured from the nearest wall. This can thenbe used to produce the distribution of the tracers based on

the proportion of tracer at a particular distance and the

number of tests performed.Figure 4 shows the distribution curves of the solid tracers

in a Deutsche Babcock grate experiment, normalized to thetotal number of tests performed. The standard deviations1forthese curves were calculated, and the mean of the calculatedstandard deviations was found to have a value close to 2.

A mathematical model has been developed to simulatethe movement of the solid material on the grate based onthe probability for a solid tracer to swap position with theadjacent tracer. This model can be applied to the movementof the solid material in three directions, i.e. axial (x),transverse (y) and normal to the grate (z).

As an example, consider the solid movement in thetransverse (y) direction only. The distance travelled by asolid tracer in the transverse direction is the result of severallocal swaps. In this model, the solid bed is divided into anumber of cells nt, as shown in Figure 5. Initially, celln isoccupied by a tracer n. In Figure 5, C(t,n) is the numberof the tracer in celln at time t. Each cell n is also given avariableP(t,n) which is a random number between 0 and 1,generated during the numerical simulation.

A sequence of `decision-making processes is carriedout across the bed, over several time steps, to determine

22 GOHet al.


Figure 1.Deutsche Babcock rotating drum grate.

Figure 2.Martin grate.

Figure 3.ABB horizontal grate.


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whether a tracer in cell n would swap position with thetracer in cell n+ 1. This sequence is as illustrated inFigure 6. In this `decision-making process, a global value

Pl is rst set for the probability for a local swap. At therst time step Dt, if probability of cell 1 at t = 0 or P(0,1)is larger thanPl, then tracer m = 1 at time t= 0 or C(0,1)will stay at cell 1 and no swapping will occur. The processthen proceeds to cell 2 where P(0,2) is compared with Plto decide whether C(0,2) will swap position with C(0,3). IfP(0,2) is again larger thanPl,C(0,2) will not swap positionwith C(0,3). The process will then proceed to cell 3.

If in the rst instance, P(0,1) is smaller than Pl, thenC(0,1) will swap position with C(0,2). The process thenproceeds to cell 3 where P(0,3) is compared with Pl todecide whether C(0,3) will swap position with C(0,4). IfP(0,3) is again smaller than Pl, C(0,3) will swap positionwith C(0,4). The process will continue at cell 5. If at theend of the sequence, there is only one cell remaining,the probability P(0,nt) will not be compared with thelimiting value, Pl. Since the tracer is already in the lastcell adjacent to the wall, no swapping will occur. This`decision-making process can start at either side of the bed.

In summary, at any timet,C(t,1) can either be C(t Dt,1)

or C(t Dt,2), depending on the values ofP(t

Dt,1) and

Pl. Similarly, C(t,2) can either be C(t Dt,1),C(t

Dt,2)

or C(t Dt,3), depending on the values of P(t

Dt,1),

P(t Dt,2) and Pl. For cell n = nt, C(t,nt) can either be

C(t

Dt,nt

1) or C(t

Dt,nt). In general, C(t,n) can

either be C(t Dt,n 1), C(t Dt,n) or C(t Dt,n+ 1),for 1


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By inserting the mean value of experimentally obtaineds into equation (1), the probability for the solid tracers toswap positions in the experiment, Pl, was obtained. Thisvalue ofPl is then fed into the mixing model to predict thestandard deviation for each tracer distribution.

Figure 8 compares the experimentally obtained and thecomputed standard deviations of the tracers. It also showsthe variation ofs with respect to distance from one of theside walls; which was used as a reference wall in thisanalysis. It is evident from Figure 8 that there is areasonably good agreement between the experimental andthe computed data. The mean of the computed standarddeviations was found to be 2.1; a value which lies withinthe 95% condence bands of the best tting curve asshown in Figure 9. This suggests that the movement of the

tracer particles in they-direction can be accurately predictedusing this technique.

The same technique can be applied to the x and zdirections and be validated against experimental dataobtained from the particle tracking experiments in therespective directions. The integration of the mixing modelin these directions will provide a three-dimensional mixingmodel which can predict the mixing process on the grateand be incorporated to a mathematical model for incine-rator waste bed combustion simulation.

MODELLING OF INCINERATORBED COMBUSTION

The physical volume of the municipal waste reducesby 90% and the mass by 70% during combustion. A suitablebed model must therefore permit simulation of the reduc-tion in the bed volume. In general, the solid waste can be

considered to consist of four components: moisture, volatile,xed carbonand ash. During incineration, moisture, volatilesand xed carbon are removed from the solid matter by thedrying, pyrolysis and gasication processes, respectively. Aphysical representation of the changeof bed volume which ismathematically linked to these three processes has beenestablished in the step change model2.

The conservation equations of the solid phase compo-nents are expressed as:

sYi

t+ =(snsYi) = =(Ds=(sYi) + Si (2)

where =u= ux/x+ uz/z for a two-dimensional simu-lation. The general expression for the energy equation ofthe solid phase may be written as:

sHs

t+ =(snsHs) = =(ls=Ts) + =qr+ Qs (3)

24 GOHet al.


Figure 6.Local swap procedure in the transverse standard deviation.

Figure 7.Probability of swapping versus computed standard deviation.


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whereqrdenotes the radiative heat ux, and the source termQs represents the overall effects of heat transfer betweengas and solid and heats of reaction of the various processesoccurring during solid incineration.

The solid velocity in the vertical direction for any controlvolumej in the bed (ns)z(j ), depends on the rate of volumereduction of the bed and can be written as:

(ns)z(j) = (ns)z(j 1) +

1

Az(j )

V

t j(4)

where

V

t =

VB

t+ VC

t+VD

t+ VA

t(5)

and B is the initial waste material,Cis the dried solids,D isthe dried and pyrolysed solids and A is the dried, pyrolysedand gasied solid (ash). The time differential equationsrepresenting the changes in volume of each material aregiven as follows2:

VB

t =

(RP)2

2v2B(1 B)

(6)

VC

t =

(RP)2[1 (1

F2)v2B]

2v

2B(1

C

)

(RP)3

3v

3C(1

C

) (7)

VD

t =

(RP)3[1 (1

F3)v3C]

3v3C(1 D)

(RP)5

5v5D(1 D)

(8)

VA

t =

(RP)5v4D5v5D(1

A) (9)

The steady-state travelling grate combustion problem maybe simplied by using an unsteady-state static bed if it isassumed that the refuse is supplied to the moving grate at aconstant rate, and there is no movement of bed materialrelative to the grate. Predicted variations with respect totime, t, using the unsteady-state static bed model can beused to predict variations with distance,x, from the pointof refuse input in the steady-state moving bed model byusing x = nxt, where nx is the local steady velocity of thegrate movement. Any variations of the conditions above

the bed and the rate of underfeed air input with respect toxfor the locally steady-state moving bed can be modelled

25INCINERATOR BED COMBUSTION


Figure 8.Variation of standard deviation (s) with distance from one of the side walls (y).

Figure 9.Comparison of the experimental result with the calculated value from the mixing model.

Figure 10.Typical gas temperature prole from unsteady state xed bedmodel.


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as variations with respect to time in the unsteady-state staticbed using t= x/nx. An example of the typical temperatureprole of the gas phase predicted by the mathematicalmodel is shown in Figure 10. This prole was obtainedassuming a constant freeboard temperature and that com-bustion of gaseous volatiles liberated during pyrolysisoccurs above the bed. Similar temperature proles wereobtained during experiments with a batch reactor (seeFigure 14). The slopes of the temperature rise in Figure 14are not as steep as those seen in Figure 10. This indicatesthat a fraction of the volatiles liberated during pyrolysisburn within the bed causing a more gradual temperature

rise.Figure 11 shows the temperature contours of the solidmaterial in the bed, modelled on a sloping grate with therefuse being fed from left to right, predicted usingthe steady-state travelling bed model. The temperature ofthe solid material in the bed gives an indication of theprocess that is occurring within the bed; drying (betweenthe wet bulb temperature and the vaporization tempera-ture), pyrolysis (approximately 540 K) and gasication(above 600 K). The locations of the processes as indicated

in the gure show close similarity to the combustion modelproposed by Kuo et al.

3. Typically, the solid waste on thetravelling grate is initially heated and loses most of itsfree moisture by the time its temperature reaches 373 K. Thedrying zone in the bed as indicated in Figure 11 correspondsto the region where the mass fraction of the moisture con-tent in the bed is decreasing in Figure 12. In Figure 11, asthe bed temperature increases further, the waste pyrolysesat about 540K and then ignites at approximately 600K.The waste eventually burns vigorously until either theoxygen surrounding the solid is consumed, or the solid isfully devolatilized leaving a carbonaceous char. The resi-

dual charred or partially charred element may undergofurther pyrolysis, be gasied by CO2 or H2O to yield COand H2, or be oxidized by O2 to form CO2.

MEASUREMENTS OF WASTE BED COMBUSTION

A good dynamic mathematical model of the incinerationprocess requires a combined knowledge of the physicalcharacteristics of the grate movements and chemical charac-teristics of the waste combustion on the grate. Combustion

26 GOHet al.


Figure 11.Contour plot of predicted solid temperature.

Figure 12.Contour plot of predicted moisture concentration.


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and kinetics data that are required for the bed modellingprogramme have been obtained from an experimentallaboratory xed bed reactor built to study the combustionof municipal solid waste, as illustrated in Figure 13. The rigconsists of a cylindrical chamber of 1.5 m length and 20 mminternal diameter. The combustion pot was designed to holdsamples of simulated waste up to 0.5 m in height from thegrate (about 2 to 3 kg). Preheated primary air is introducedthrough a distributor plate (i.e., the grate) at the bottom ofthe chamber. The bed is ignited at the surface and theprocess fronts advance from the top of the bed to the grate.The chamber is mounted on a weighing scale to permit theburning rates to be determined. Temperatures and gascomposition measurements at xed positions above thegrate are also made. An example of the temperaturemeasurements obtained during a typical preliminarycombustion experiment are shown in Figure 14. As thethermocouples are located at xed positions within the fuelbed, the approach of a reaction front to each position isshown by the sharp increase in the temperature measured.

The corresponding change in the solid mass in the bed isas illustrated in Figure 15.

The gas composition in the reactor at 430 mm above thegrate is as illustrated in Figure 16. The time for the increasein CO (to above the range of the gas analyser) and CO2concentrations and the reduction in O2concentration in thisposition correspond to the time for the bed temperaturerise as depicted in Figure 9. This notable change is theignition front and is due to the ignition of the gaseousvolatiles that are liberated during the pyrolysis process.Figure 16 also shows that concentration of NOx in thisposition is also seen to gradually increase to a maximum

value of approximately 150 ppm before reducing to about100 ppm. The NOx concentration increases because thegases coming up to the sampling point contain NOxthatis formed during devolatization of the waste. As the layerof char close to the surface of the bed passes below thesampling point, the concentration of NOxdecreases slightly.

This decrease in NOx concentration can be attributed tothe reduction of NOx in the char layer where CO and NOxcan react to form CO2and N2using the carbon in charas catalyst for the reaction4.

Experimental investigations on the xed bed reactormust be complemented by studies on a full-scale incineratorplant. In addition, development work on a suitable mathe-matical model for incinerator bed combustion is far fromideal without comparisons with experimental data andmeasurements from a full-scale plant to conrm the validityof the approach used in the model. Conventional measuringtechniques only allow full scale plant data to be obtainedfrom xed positions in the plant, mainly in the freeboardregion and not inside the burning bed.In-situ instantaneousmeasurements of temperature, radiation and gas composi-tion inside a burning bed in a full-scale incinerator plantare therefore difcult and often restricted for manyreasonssize and integrity of the affordable measuringinstrument, safe access, etc.

The requirement for accurate solid bed combustion

data for the bed model validation, particularly within thesolid waste in large incinerator plants, has initiated the



Figure 13.Schematic diagram of the xed bed reactor.

Figure 14.Gas temperatures above the grate.


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development and construction of a prototype measuringinstrument. This prototype instrument consists of a familyof built-in electronic sensors and a recording memory unitor a mini chip installed in a refractory bre or ablatingresin capsule about 12 to 15 cm in diameter and length. Itcan record a variety of measurementstemperature (usingthermocouples), radiative ux (using a thin sapphire rodas a bre optic element), and gas composition (e.g. CO2,CO, O2) (using a phosphoric acid based electrochemicalcell), for the duration of the test, e.g. one hour, dependingon the thermal properties of the capsule and unit design.

The instrument as shown in Figure 17 is uniquely differ-

ent from the instruments currently commercially available

as it can be introduced into the incinerator with the wastefeed and tumbles along with the burning waste material.The unit thus experiences the same high temperature condi-tions as the waste material, whilst measuring and recordingthe temperatures, gas composition and heat uxes in theburning bed. At the end of the process, the capsule can berecovered at the incinerator exit, and the data stored inits memory unit can be downloaded to a computer. The

recorded data or process variables can then be saved toa common delimited le, or copied to another existingcommercial package such as a spreadsheet, statisticalpackage or a word processor. The electronic instrumentwithin the capsule can be reused by refurbishing itsprotective casing and the whole measuring procedure canbe repeated several times so that the mean and standarddeviation of the measured process variables can be deter-mined. Thus, data on the statistical variability can beobtained through random motion of the unit with the wasteand not through standard measurements from a xedpoint in the plant, e.g. a boiler ue.

The size of the instrument must be optimized to exploitfully the thermal properties of the insulating material andgeometrical design. To reduce the heating rate to the coreof the instrument, the ratio of the exposed surface areaper unit volume must be minimized. For a simple thermalinsulation system, the heating rate by conduction to theunit,q, assuming quasi-steady state, is given by:

q = 2lp(To Ti)

(hiro hori)

(ro ri)ln(hiro/hori)

+ 2riro(ho

h1)

(10)

where, ho, hi, ro and riare the dimensions of the capsule

as depicted in Figure 17.The operating time of the instrument in each test depends

on the rate at which heat is transferred to the core and themaximum allowable operating temperature of the electro-nics within the unit. To increase the operating time whilesimultaneously maintaining a low internal temperature, aheat sink can be incorporated into the design. Preliminarytesting of the system in a furnace at more than 10008C withplaster material and water as the heat sink demonstrateda working life of more than one hour as shown in Figure 18.This is sufcient for measurements in an incinerator sincemost incinerators operate with a residence time of aboutone hour.

28 GOHet al.


Figure 15.Change in bed mass with time.

Figure 16.Gas concentration at 430mm above the grate.

Figure 17.Schematic of the prototype heat resistant capsule.


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MEASUREMENTS AND MODELLING OFSECONDARY JETS IN AN INCINERATOR

In present practice in incinerators, secondary air jets arelocated above the bed to burn out hydrocarbons and carbonmonoxide. It is observed that slag tends to build up roundthese jets, and in time the jets are often completely closedoff. The build-up of slag around the jets is a major problemin the operation of incinerators. This slag can accumulateto a thickness of about one metre with a weight of severaltonnes. The accumulation can reduce the availability of the

plant and it also gives a safety problem since injury can becaused when the slag is removed by pneumatic drill during

maintenance operations. More importantly, the jets areoften located in a critical mixing region in the incinerator,i.e. in the throat region between the furnace chamber andthe radiation shaft, and the thick slag layer alters the owdynamics in this critical region where secondary air orrecycled ue gases are introduced.

Slag is formed when molten y ash particles whichare entrained into the jet ow impinge near the mouth of

the nozzle. The angle of the turn of the entrained ow inthe vicinity of the jet mouth is particularly sharp. Someof the particles will have sufcient inertia not to be draggedalong with the jet. The inertia of these particles will leadto them impinging on the wall as shown in Figure 19.Since some of the lower melting point particles can bemolten at this stage, they will stick rather than bounceoff, thus initiating the slag layer. Once the slag layerbegins accumulating, even particles that are not moltenor sticky are more likely to be captured

5. The solid slag

will then gradually build up until the thermal resistanceof the layer is such that the surface is molten. Particles

with a higher melting point can then stick and the rateof build-up can be expected to increase. Eventually, theinertia of the particles causes the layer to build up untilthe jet is closed off.

The ow eld around a high velocity jet penetrating alow velocity cross ow has been experimentally investi-gated in a wind tunnel specially designed to minimizethe turbulent intensity at the main ow inlet. The ink dotow visualization technique6 was used to obtain visiblestreak lines on acetate lms that reveal the surface owpatterns.

Figure 20 shows the surface ow pattern of a 7 mm dia-

meter nozzle with a jet momentum ux ratio of 65 wherethe jet momentum ux ratio J, is dened as7:

J =(u

2)jet

(u2)flow(11)

It is evident in Figure 20 that the uid from the mainow around the jet is entrained towards the mouth of the jet.

To prevent the process of slag build-up, the ow eldaround the jet region must be reversed. This can be achievedby tting a deector near the mouth of the jet to redirectsome of the ow parallel to the wall as depicted in Figure 21.The purpose of the deector is to skim off the outer layer

of the jet and redirect it tangentially to the surface of thewall.



Figure 18.Change in core temperature with time.

Figure 19.Onset of slag formation.

Figure 20.Surface ow prole around a jet.


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Figure 22 shows a surface tracing of the same nozzleand ow conditions, but with a de ector attached. Thedeector had an orice diameter of 0.9 jet diameters, anda height of 0.6 jet diameters above the at plate. It can beseen that the addition of the deector clearly alters the oweld. Under these ow conditions, the de ector movesthe area of separation in front of the nozzle 1.9 jet diameters

away from the leading edge of the nozzle. There is nowan area around the nozzle swept out by redirected owdue to the deector. The darkened area seen near the for-ward facing mouth of the nozzle is due to recirculationof ow in this area, which prevents the ink from beingblown away from the mouth of the nozzle.

Computational Fluid Dynamics simulation under thesame conditions revealed the recirculation zone underthe deector as shown in Figure 23. The uid from thecross ow containing molten particles is no longer beingentrained into the jet but is forced away by the ow fromthe main jet, hence reducing the probability of particleimpingement near the mouth of the jet. This recirculationis likely to depend on the height of the deector and hencethe deector distance from the nozzle must be optimized tominimize the recirculation. Further design to improve andoptimize the deector design, and hot combustion experi-ments with simulated y ash, are currently under way.

CONCLUSIONS

Incineration is now accepted as the most environ-mentally friendly means of disposing of municipal solid

waste, and the design of incinerators must be optimized.In the past, the design of incinerators has not been basedon fundamental understanding and modelling of the pro-cess, and empirical rules have had to be used. The topicis now receiving increased attention from the engineeringresearch community, and the gap between fundamentalscientic principles and plant construction and operationis now being bridged. Municipal waste incineration

research carried out at SUWIC is focused on improvingthe design of municipal solid waste incinerators so thatfuture plants can be designed and operated in the mosteffective manner possible.

Mixing is the key factor to ensure complete combustionof solid waste in an incinerator burning bed. Existing gratesystems do not produce a uniform waste distribution,resulting in channelling of ow through the bed and ahigh excess air requirement. A mathematical mixing model,based on the probability for a tracer particle to swap posi-tion with an adjacent tracer on a travelling grate, has beendeveloped. In parallel with the model development, the

grate mixing process has been quantitatively determinedby a series of systematic particle movement experimentson scaled models of three of the most common industrialgrates. Comparison between experimental and computeddata has shown good agreement. The grate mixing processcan be quantied and accurately modelled in a systematicnumerical procedure based on `swap probability. Theimportance of the probability parameter is that it uniquelycharacterizes the `random walk mixing and is essentiallyindependent of factors such as particle position and gratelength.

A comprehensive model of the burning bed of municipal

solid waste based on the key processes in a waste bed hasbeen developed in order to provide more accurate data thanpresently available on the boundary conditions at the bedsurface. This information is required for use in the CFDmodelling of the gas phase. In the next stage, the mixingmathematical model will be incorporated into the presentbed model to improve the prediction of the incinerator bedcombustion. The model developed for dynamic simulationof a xed bed has been expanded for modelling the steadystate combustion process on a travelling grate incinerator.The present analysis is limited in certain respects and

30 GOHet al.


Figure 21.Annular deector t o p revent slag formation.

Figure 22.Flow prole with annular deector.


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improvement to the bed combustion model requirescombustion data acquired from a laboratory-scale xedbed reactor as well as full-scale incinerator plant. To acquire

high quality plant data, a prototype measuring instrumentis currently being developed. This instrument can be usedto collect the plant data within the burning solid waste bedin the incinerator.

Another key area to improve the incinerator plant efci-ency is to prevent the formation of slag. At present, slagformation around the secondary air jets in the incineratorposes a major operation problem. SUWICs research alsosuggests that the formation of slag around secondary air

jets can be prevented by installing an annular deectoraround the jets.

NOMENCLATURE

Az control volume cross-sectional area normal to z directionC(t,n) tracer particle in celln at time t

Ds solid diffusion coefcientF2 fraction of the waste volume occupied by water which is replaced

by pores during dryingF3 fraction of the waste volume occupied by volatile matter which

is replaced by pores during pyrolysishi capsule core heightho capsule external height

Hs solid sensible enthalpyj control volumeJ jet momentum ux ratiom tracer number

M solid massn cell numbernt total number of cellsPl swapping probabilityP(t,n) random number generated for celln at timetqr radiative heat uxq conductive heat ux to capsule core

qo convective heat ux to ablating surfaceQs source term for enthalpy balance equationri capsule core radiusro capsule outer radius(Rp)i rate of removal of componenti, wherei = 2, 3, 4, 5 or 6s standard deviationSi source term for component mass balance equationTi temperature of the internal surfaceTs solid temperatureTg gas temperatureTo temperature of the external surfacet timeu uid velocityns solid velocitynx moving grate velocityV total volume of solidVL volume of solid material L, whereL = A, B, Cor D

x axial directiony transverse direction

Yi mass fraction of componentiz direction normal to gratel thermal conductivity of the capsule materialls solid effective thermal conductivity uid densitys solid densityi density of componentiL void fraction of materialLviL volume fraction of componenti in material LDt time increment

Subscripts2 moisture3 v olatil e matt er

4 bound ash5 xed carbon6 free ashA dried, pyrolysed and gasied materialB raw waste materialC d ried mat erialD dried and pyrolysed material



Figure 23.Velocity vector plot for ow eld prediction.


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REFERENCES

1. Spiegel, M. R., 1972, Theory and Problems of Statistics, ShaumsOutline Series in Mathematics (McGraw-Hill Publishing C ompany)Chapters 4, 13 and 14.

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ACKNOWLEDGEMENT

The authors would like to thank the Eng ineering and Physical SciencesResearch Council (EPSRC), Kingseld Electronics Ltd., Shefeld Heatand Power Ltd., Shefeld Municipal Solid Waste Incinerator Plant UK and

ABB Corporate Research (Switzerland) for their nancial and technicalcontributionst o this project.

ADDRESS

Correspondence concerning this paper should be addressed toDr Y. R. Goh, Department of Chemical and Process Engineering,University of Shefeld, Mappin Street, Shefeld, S1 3JD, UK.

This paper was presented at the 2nd International Symposium on

Incineratio n and Flue Gas Treatment Technolo gies, org anized b y ICh emE

and held at the University of Shefeld, UK, 46 July 1999.

32 GOHet al.

Trans IChemE Vol 78 Part B January 2000

Documents

Y.R. Goh; C.N. Lim; R. Zakaria; K.H. Chan; G. Reynolds; Y.B. Yan -- Mixing, Modelling and Measurement