8
Robotic Machine for High-Quality Shotcreting Process PhD, Samir Nabulsi, AITEMIN, Margarita Salas 14, 28918 Leganés (Madrid), Spain Mr, Angel Rodriguez, AITEMIN, Margarita Salas 14, 28918 Leganés (Madrid), Spain PhD, Olga Rio, CISDEM, CSIC-UPM, Serrano Galvache 4, 28033 Madrid, Spain Abstract This paper summarizes the development of the technologies used to produce high quality sprayed concrete layers by ro- botizing a commercial shotcreting machine and automating the process used in the tunnelling construction industry. The proposed method provides the control system with the information of the properties of the pumping process, controlling the quality of the concrete layer by adjusting in real-time the trajectory of the shotcreting machine. Given the unstruc- tured nature of the tunnelling construction method there is an inherent difficulty in the automation of the shotcreting process. A complete description of the implemented control architecture of the shotcreting machine, the automated shot- creting process, the real-time quality layer prediction and the analysis of the tests made in real sites are shown in this pa- per. 1 Introduction In the underground construction branch of civil engineer- ing and mining there are different types of tunnelling methods, and one of the major ones, known as drill & blasting, often include the process of concrete spraying -or shotcreting- process. This tunnelling method consists of three main stages: Drilling and blasting, loading and haul- ing of blasted rock and supporting of the newly open cav- ity. In the third step, shotcreting is often the method of choice for providing temporary support. This process consists on spraying concrete mix on the sur- face of the new cavity, quickly creating a supporting struc- ture. The shotcrete surface can be used as temporary sup- port until a final concrete lining is cast, or even as the final lining of the tunnel if additional structural shotcrete is added. Nowadays, for performing the shotcreting process special- ized machinery is controlled by qualified operators, which create shotcrete layers of specific properties based on their experience. The properties and the quality of the layer de- pend on the type of the lining needed, and basically the quality of the layer is measured in terms of homogeneity and thickness. In the last years there has been an increasing interest on the real time determination of both the homo- geneity and thickness of shotcrete layers. There are both technical and economical reasons that justify this interest: On the one hand there is the need of guaranteeing a mini- mum shotcrete thickness [1], while having the minimum required structural strength. On the other hand, contractors also do not want to place extra shotcrete on the walls, for usually they will not get paid for it. Additionally the development of different acquisition technologies during the past few years has made plausible the introduction of automation techniques in the under- ground construction process. Different approaches have been described for shotcreting automation and thickness estimation [2][3][4]. The proposed method provides the control system with the information of the properties of the pumping process, controlling the quality of the concrete layer by adjusting in real-time the velocity of the trajectory of the shotcreting machine. Figure 1 Sika®-Putzmeister PM-407 [5]. The industrial machine Putzmeister-Sika® PM-407 (see Fig. 1) has been used as a test platform for the develop- ment of the shotcrete automation. 2 Process automation and control system of the shotcreting machine In tunnelling, after the advancement (drilling and blasting) stage, shotcrete is used to cover the surface of the roadway to create a support on the working area inside the tunnel. The advancement stage is made by introducing explosives in the face of the tunnel and making a controlled blast. But, as controlled as the blasting can be, the dimensions of the resulting surface are completely unstructured and thus, one of the implicit difficulties involved in the shotcreting proc- ess that has avoided its automation. Three steps have been defined for the automated shotcret- ing stage: ISR / ROBOTIK 2010 1137

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Robotic Machine for High-Quality Shotcreting Process PhD, Samir Nabulsi, AITEMIN, Margarita Salas 14, 28918 Leganés (Madrid), Spain Mr, Angel Rodriguez, AITEMIN, Margarita Salas 14, 28918 Leganés (Madrid), Spain PhD, Olga Rio, CISDEM, CSIC-UPM, Serrano Galvache 4, 28033 Madrid, Spain Abstract This paper summarizes the development of the technologies used to produce high quality sprayed concrete layers by ro-botizing a commercial shotcreting machine and automating the process used in the tunnelling construction industry. The proposed method provides the control system with the information of the properties of the pumping process, controlling the quality of the concrete layer by adjusting in real-time the trajectory of the shotcreting machine. Given the unstruc-tured nature of the tunnelling construction method there is an inherent difficulty in the automation of the shotcreting process. A complete description of the implemented control architecture of the shotcreting machine, the automated shot-creting process, the real-time quality layer prediction and the analysis of the tests made in real sites are shown in this pa-per. 1 Introduction In the underground construction branch of civil engineer-ing and mining there are different types of tunnelling methods, and one of the major ones, known as drill & blasting, often include the process of concrete spraying -or shotcreting- process. This tunnelling method consists of three main stages: Drilling and blasting, loading and haul-ing of blasted rock and supporting of the newly open cav-ity. In the third step, shotcreting is often the method of choice for providing temporary support. This process consists on spraying concrete mix on the sur-face of the new cavity, quickly creating a supporting struc-ture. The shotcrete surface can be used as temporary sup-port until a final concrete lining is cast, or even as the final lining of the tunnel if additional structural shotcrete is added. Nowadays, for performing the shotcreting process special-ized machinery is controlled by qualified operators, which create shotcrete layers of specific properties based on their experience. The properties and the quality of the layer de-pend on the type of the lining needed, and basically the quality of the layer is measured in terms of homogeneity and thickness. In the last years there has been an increasing interest on the real time determination of both the homo-geneity and thickness of shotcrete layers. There are both technical and economical reasons that justify this interest: On the one hand there is the need of guaranteeing a mini-mum shotcrete thickness [1], while having the minimum required structural strength. On the other hand, contractors also do not want to place extra shotcrete on the walls, for usually they will not get paid for it. Additionally the development of different acquisition technologies during the past few years has made plausible the introduction of automation techniques in the under-ground construction process. Different approaches have been described for shotcreting automation and thickness estimation [2][3][4]. The proposed method provides the control system with the information of the properties of the

pumping process, controlling the quality of the concrete layer by adjusting in real-time the velocity of the trajectory of the shotcreting machine.

Figure 1 Sika®-Putzmeister PM-407 [5].

The industrial machine Putzmeister-Sika® PM-407 (see Fig. 1) has been used as a test platform for the develop-ment of the shotcrete automation.

2 Process automation and control system of the shotcreting machine

In tunnelling, after the advancement (drilling and blasting) stage, shotcrete is used to cover the surface of the roadway to create a support on the working area inside the tunnel. The advancement stage is made by introducing explosives in the face of the tunnel and making a controlled blast. But, as controlled as the blasting can be, the dimensions of the resulting surface are completely unstructured and thus, one of the implicit difficulties involved in the shotcreting proc-ess that has avoided its automation. Three steps have been defined for the automated shotcret-ing stage:

ISR / ROBOTIK 2010

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1. Pre 3D LADAR scan of the working area. 2. Automated shotcreting process. 3. Post 3D LADAR scan and layer quality evalua-

tion.

The first step of the automated process is basically done by imaging the working surface of the tunnel with a 3D LADAR scanner (the LIDAC-16 developed by AITEMIN). The information acquired from the first scan is then used by the main control system of the machine to generate the trajectories to shotcreting a layer. Finally a second scan is made in order to evaluate, subsequently, the quality of the layer and the amount of concrete used. This information can also be used to optimise the control parameters of the automatic shotcreting system.

2.1 Robotization of the shotcreting machine The shotcreting machines are based on manipulators that as an end tool they have a nozzle to spray the concrete fed by a concrete pump. It is to be noted that the best way to spray the starting mix into a wall is by keeping the spray-ing vector perpendicular to the surface of the selected area, at a certain distance that may vary between 1 and 1.5m. Furthermore this type of machinery hasn’t been designed for automation purposes but for manually controlled la-bour. This implies that some additional factors like me-chanical deformations, backlashes, or the control type of the actuators have to be taken into account in the control system of the machine for precise positioning. The proposed control system has been designed to use the real-time layer thickness estimator and the roadway ge-ometry information to feedback and adapt the trajectory control according to the conditions in order to produce high quality concrete layers.

2.1.1 Mechanical configuration of the manipula-tor

The arm of the shotcreting machine is made of 5 degrees of freedom (DOF) of hydraulically actuated joints (see Fig. 2). The first three are configured as a spherical ma-nipulator (2 rotational and 1 prismatic joint), and the last two rotation joints from the end tool, are specially config-ured to help the operators to maintain a certain orientation without having to move many joints simultaneously. There is an additional sixth joint at the end of the tool that generates an eccentric rotation of the nozzle. This joint was originally design to help the operators to increase the smoothness of the spraying, but it is not going to be taken into account for automatic control purposes and it is con-sidered the nozzle in the centre. Another property of the system is that it is only possible to control the velocity of the first two DOF according to the control type of its hydraulic valves (see Table 1). The rest of them they just have on/off valves. This configura-tion affects the way the velocity of the movement of the manipulator is controlled (as explained later in section 2.1.2.2).

Figure 2 D-H configuration of the PM – 407 manipulator.

Table 1 D-H Parameters for shotcreting manipulator.

The direct kinematics of every joint is known by applying the Denavit-Hartemberg [6] convention, according to the joint configuration (see Table 1), where the target position will result by adding to a6 the desired distance between the nozzle and the tunnel surface (r). But to control the manipulator in position, velocity and orientation accord-ing to desired target position vector (P), by evaluating its inverse kinematics, some details have to be taken into ac-count.

a. b. Figure 3 Yaw (ψ) and pitch (ϕ) angles of the nozzle dur-ing spraying. a) Top view and b) Front view. First of all, P(O6r,R(ψ,ϕ)) is a vector defined by two ele-ments, the position (X,Y and Z) of and the attitude (ψ,ϕ) for the target of spraying; this elements are specified ac-cording to the coordinate system of the origin of the ma-nipulator (Oo) (see Fig. 3), and they are provided by the LADAR system. The inverse kinematic problem has been solved using the decoupling technique [7]. As in this problem O6 and the orientation of the nozzle are known, it is possible to solve the position and orientation of the nozzle by evaluating O5 using an analytical approach by the given equation:

Joint i α i a i θ i d i Ranges Control Type

1 π/2 -a 1 θ 1 d 1 -158o - 171oProportional

2 π/2 0 θ 2 0 19o - 154oProportional

3 0 a 3 0 d 3 0 - 2094 mm On/Off

4 π/2 0 θ 4 0 0 - 360oOn/Off

5 0 0 θ 5 -d 5 -47o - 204oOn/Off

6 0 a 6 0 0 - -

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x5 = x6 – (a6Cos(ϕ)* Cos(ψ)) y5 = y6 – (a6Cos(ϕ)* Sin(ψ)) z5 = z6 + a6Sin(ϕ)

The inverse kinematic problem must proceed finding O3. Given the fixed distance O63 = sqrt(a6

2 + -d52) and its ori-

entation γ = atan(-d5,a6), O3 can be directly solved by the equations:

x4 = x3 = x6 – (O63Cos(γ+ϕ)* Cos(ψ)), y4 = y3 = y6 – (O63Cos(γ+ϕ)* Sin(ψ)), and z4 = z3 = z6 + O63Sin(γ+ϕ).

Then, the three first parameters can be evaluated just with the position of O3, indeed θ1 = Atan(O3y ,O3x). In this case there is just one solution for θ1 because of the constraint on the joints. Normally θ1= Atan(O3y ,O3x)+ π is also a possible solution but if this solution is chosen, it will give automatically a negative solution for θ2 and this is not al-lowed by the constraints of the machine. Hence, there is just a unique θ1 it is possible to evaluate O1 according to the next equation:

O1 = (-a1Cos(θ1), -a1Sin(θ1), L1),

and so is the distance O31. According to this the distance of the prismatic joint can be evaluated by d3 = sqrt(O31

2-a3

2), and finally, θ2 can be evaluated by the equation:

θ 2 = Atan(n,q)-Atan(a3,d3) + π /2 where n = O3 -O1 projected on y1 and q = O3 -O1 projected on x1. Now that θ 1, θ 2 and d3 have been found, the transforma-tion matrix T0

3 can be evaluated and therefore the position and the orientation of O3 are known. Moreover, the matrix between the O3 and O6 is also known according to the transformation matrix T3

6. In this way it can be deter-mined that θ4 = Atan(T3

6(1,3),-T36(2,3)) and θ5 =

Atan(T36(3,1), T3

6(3,2)). The problem with this method is that in order to be cor-rect there is a condition that has to be fulfilled and it is that z3 must be perpendicular to z5 and therefore to z6. This is determined by the geometry configuration of the manipulator and in fact there are very few circumstances in which this condition coincides with the previous in-verse kinematic evaluation. Therefore it is necessary to find an O3 that may fulfils the perpendicular condition between z3 and z6. This problem is solved by recursive iterations where the reference system O6 = O6*Rz(φ) (where Rz(φ) is the rotation matrix or the roll angle of the nozzle ) is rotated around z6 until the dot product z3. z6 = 0. This means that the link between O3 and O5 is rotated around z6 adding in each iteration a constant value to φ, changing the position of O3 and O1, and therefore chang-ing the value of θ1, θ2, d3, θ4 and θ5. Each of these posi-tions must be evaluated every iteration, according to the equations shown before, until the perpendicular condition is satisfied.

This process may take to much CPU time if it is not done with certain logic. For example the direction of the rota-tion may be selected according to the attitude of the noz-zle and the quadrant where it is located. Additionally, the time of the process may decrease by in-creasing the rate of φ and using statistical strategies to av-erage the value of the product between iterations. This is the case when, for example, the value of the dot product passes through zero between iterations.

Figure 4 Flowchart for the inverse kinematics resolution for the shotcreting machine’s manipulator.

2.1.2 Control architecture The main control is based on a computer (master control-ler) which, through the information provided by multiple sensors and measurement systems, is responsible for mov-ing the arm of spraying at a determined velocity by evalu-ating the position and attitude of the nozzle tip with re-spect to the surface of the tunnel, having defined previ-ously the work area and the thickness of the layer. It has a distributed structure which is designed to inter-connect the interfaces that are designed to monitor and control the shotcreting machine, its manipulator and to add additional control elements (see Fig. 5). It is divided in four main modules: the manipulator’s in-terface, the pumps’ interface, the additional elements (LADAR scanner or the remote control), and the main controller that has a visual based Human Machine Inter-face (HMI), designed for its use in construction sites, and that it is in charge of the control system of automated shotcreting process. The system is capable of running in three modes of opera-tions: a) Automatic mode where the complete process is done in an autonomous process; b) Semiautomatic mode, where the operator can move the manipulator using a re-mote control but is assisted by the main control system in order to guide him to maintain the correct attitude and po-sition of the nozzle according to the surface of the tunnel;

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and c) the manual mode, that is the last mode of opera-tion, where the operator uses the remote control to move freely the manipulator but it is assisted by the control sys-tem in order to move the joints with coordinated move-ments instead of one joint at a time (as it is done in the operation without any automation).

Figure 5 Main control architecture. The last two modes of operations were implemented in case unexpected issues arises inside the tunnel construc-tion process (like faults or water leaks) and the automated control system is not able address them. These modes won’t be discussed further in this document.

2.1.2.1 Main controller and HMI The main controller is based con an industrial PC and it is designed to control the automated shotcreting process in-teracting with the different interfaces and additional com-ponents of the installed on the machine. The windows based control application (see Fig. 6) is de-signed to be used by construction workers and provides the user with a user friendly HMI which is accessible through a touch screen panel.

Figure 6 HMI controller.

It has a main VRML model of the manipulator (1) that shows its position in real time during the automated shot-creting process. It can also be configured to monitor the progress of the process while moving the manipulator in semiautomatic or manual operation mode. Maybe this functionality doesn’t make much sense if the main controller is installed onboard; but one of the main objectives of the complete development is to prevent that the operator gets near the working area and may be able to operate from a remote location, as it is intended in fur-ther developments. The application also has an independent control for each joint (2), high level macros for different operations like the automated shotcrete process or locating the manipula-tor by entering the desired position and attitude according to the machine’s coordinates (3), and different options for the system configuration (4).

2.1.2.2 Manipulator’s interface The interoperability between the application software and the movement of the manipulator’s joints is made by an interface (see Fig. 6) which main functionality is based on a motion control card, which has a dedicated PID filtered position and velocity control for the proportional actuated joints, and has been programmed to accurately process a time based control of the position of each on/off actuated joint (see Table 1). It also provides the control software with the information of the different encoders and positions sensors and it has been programmed to evaluate the velocity of each joint in order to get to the desired position making coordinated movements at the desired velocity. This interface was designed to minimize the main CPU time of usage for processing low level information. The configuration makes suitable the use of the main control-ler with non real-time based operation systems. It is connected to the main controller through an Ethernet which is intended to which minimize the signal distortion produced by external noise sources, but instead it decreas-ing transfer rate. Nevertheless the transmission rate is made between 100 and 200 samples per second. So when the an automated spraying process has to be made, first the complete set of target positions and the shotcreting speed is evaluated a priori by the main con-trol system and then sent to the motion control card. Dur-ing the spraying the desired velocity can be modified in real time in order to adapt the spraying according to the mix pumpability conditions, meanwhile it feedbacks the main controller with the position of the joints of the ma-nipulator to visually monitor the process from the HMI.

2.1.2.3 Pump’s interface This interface (see Fig. 6) has been designed only to measure the different values used to evaluate the amount and the velocity of the pumped concrete and send them to the main control system through an USB connection. A set of sensors have been installed in the machine in or-der to measure different parameters (pressure, concrete flow, etc.). These parameters are measured not only for quality control purposes, but also for detecting the pump

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needs for a ging parameteIn this case iin charge of cording to thIn order to gface is basedtion for fast pumping par5000 sampleused).

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20s, which fris fair to say

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Figure 10 Shshotcreting bAutomatic sh According toduring varionotable the dmaintained bb). The operatormanipulator,tion of the nomay lead toquently to thOn the othermatic sprayintion and attituThere are imshotcrete thaon/off positiothe hydraulicenough to msired speed ature. This mathis level of ess.

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hotcreting trajb) Sample of ahotcreting ima

o the results gous shotcrete differences beby the operato

r has to contro thus it is easiozzle than the the radial ae semi-spheric

r hand, it is alsng it is possibude of the nozmprecise posat are caused on control of c supply of th

move all the jand the mechaay lead to posprecision is a

ckness estimion of the thsing the resulses in a determfitness of the

rface of the tue Fig. 11). Byate the differee to find the

ocess.

ummary of sp

c.

ectory exampautomatic shotage.

given by the moperations (s

etween the attior a) and the

ol independenier for him toe rest of the joattitude of thecal geometry so noticeable ble to maintaizzle during thsitions encoumainly by ththe prismatic he manipulatooints simultan

anical deformasitions errors oadmissible for

mation hickness of thlts of differen

mined test areae estimation, unnel has beeny using a commences of the th

amount of c

prayed volume

ples. a) Operattcreting and c)

measurementssee Figure 10itudes of the nautomated p

ntly each joint move the lasoints. This site boom and cof the sprayinthat with the

in the correct e whole proce

untered duringhe difficulty i

joint, the facor is not powneously at thations of the sof up to 50mmr this kind of

he layer has nt automatic a. in every spra

n scanned witmon squared

hickness estimconcrete used

e estimations [

tor’s )

s made 0) it is nozzle

process

of the st rota-tuation conse-

ng. auto-posi-

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m, but proc-

been shot-

aying th the func-

mation d in a

[8].

FiguimagIt cafromthe euppetimeestimthe omorebetw

6Therusingthe amanualso Nevedesigpectesion smoothe propOn testimseveaccostartione tFinacarriautomnel cstep botizThisfor tproccostsprovoper

ure 11 Differeges [1]. n be noticed f

m stage #1 dateffect of wireer part of the . For this rea

mated volumeother hand, ese accurate and

ween the measu

Conclure is a notableg robotizationanalysis of theual and the anoticed on theertheless, the gned for autoed difficultiesof its movem

othness of theshotcrete man

portional contrthe other handmation, deducral advantage

ount the possibing mix or anto other jobsitlly and as a ried out to memation of theconstruction iin the implem

ze heavier shomay provide

the developmess, which ms and quality

ving the workrators inside th

ence between t

from Table 2 a seems less a

e mesh and laworking are

ason, and moe are closer thstimations frod the maximuured and the e

sions ande improvemenn techniques te differences iautomated proe real shotcretrobotization mation purpos. For exampments are adee trajectory mnipulator enorols in all its jod, the models ced from empes like the factble variations

ny other circumte. result of the deasure the diffe shotcrete proindustry, it is

mentation of thotcrete machin

the industry went an unstru

may lead to theof the tunne

king conditionhe construction

two successiv

that the volumaccurate. This

ack of scannina before spra

ost probably, han the measuom the stages um error of thestimated volu

d future wnt in the qualitthat are not oin the positionocess, but theted surfaces. of a machine

oses usually ple, even thou

equate for thismay be improvough hydraulioints. presented for pirical equatit that they do

s caused by chmstances that

different expeferent possibiocess may offs planned to he method an

nery. with a standar

uctured tunnele optimisation

el support layns and the sen site.

ve 3D scanned

mes estimateds is caused byng data in theaying for firstthe values of

ured ones. On#2 and 3 are

he differencesume is 5l.

work ty of the layeronly shown inn between theey have been

e that it is notpresents unex-ugh the preci-s process, theved by givingic power and

the thicknessions, presents not take intohanges of thet change from

rimental testsilities that thefer to the tun-take the nextd use it to ro-

rdised systeml constructionn of time ander, while im-

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Page 8: Robotic Machine for High-Quality Shotcrete Processdigital.csic.es/bitstream/10261/25196/1/Robotic machine for high... · Robotic Machine for High-Quality Shotcreting Process PhD,

7 Acknowledgements The authors want to express their thanks to all AITEMIN and CSIC collaborators involved in the experimental pro-gram. Thanks are also extended to J.A. Nieto and M. Eck-stein of Putzmeister España for their support in the senso-rization of shotcreting machines; and to J.L. Rivas of SIKA España and his team, as well as to Fundación Santa Bárbara staff for their collaboration in the implementation of the experimental program. The work presented here was partially funded by the Spanish ministry of Science (Projects TUNPRO, BIA 2004-05562-C02-00, PIA12008-0 Ex.829370 and Project BOHEC, BIA2008-06673-C02-00/01/02)) and by the EU under the FP6 (TUNCONSTRUCT, IP-011817-2).

8 Literature [1] Rodriguez A., O. Río, S. Nabulsi: Technology Inno-

vation in Underground Construction. Chapter 19: "Real-Time Monitoring of the Shotcreting Process", Taylor and Francis 2009, pp: 373-388.

[2] Girmscheid, G., S. Moser: Fully Automated Shotcrete Robot for Rock Support. Computer-Aided Civil and Infrastructure Engineering 16, 2001 pp. 200-215

[3] Bracher, G.: CAS Computer Assisted Spraying of Wet Process Sprayed Concrete, Tunel ROČNÍK, č. 2. 2003.

[4] Melbye, R. Dimmock, K.F. Garshol: Sprayed concrete for rock support 9th Edition Degussa-MBT, Winter-thur, Swiss. 2001.

[5] Putzmeister Iberica S.A. 2009 http://shotcrete.putzmeister.es/pm407i.html [6] Denavit, J. and R.S. Hartenberg: A kinematic notation

for lower-pair mechanisms based on matrices, Trans ASME J. Appl. Mech, 23:215-221, 1955.

[7] Spong, M. and M. Vidyasagar, Robot Dynamics and Control, Wiley, New York, 1989.

[8] Rodriguez A., S. Nabulsi, O. Río: A method for esti-mating thickness of sprayed concrete layers from pumped volume. EURO-TUN 2009: Computational methods in tunneling, Bochum, September 2009, Vol II, pp: 875-881.

[9] Río, O. and A. Rodriguez: On the real time assessment of pumping mixes under actual or quasi-actual condi-tions. 3rd International RILEM Symposium on Rheol-ogy of cement suspensions such as Fresh Concrete. RILEM Publication PRO 68. August 2009. pp: 97-104.

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