Powder Technology 225 (2012) 118–123

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3D numerical study of particle flow behavior in the impinging zone of an OpposedMulti-Burner gasifier

Chao Li, Zhenghua Dai ⁎, Weifeng Li, Jianliang Xu, Fuchen WangKey Laboratory of Coal Gasification of Ministry of Education, East China University of Science and Technology, Shanghai 200237, PR China

⁎ Corresponding author. Tel.: +86 021 64250784; faE-mail address: chinadai@ecust.edu.cn (Z. Dai).

0032-5910/$ – see front matter © 2012 Elsevier B.V. Alldoi:10.1016/j.powtec.2012.03.044

a b s t r a c t

a r t i c l e i n f o

Article history:Received 30 November 2011Received in revised form 21 February 2012Accepted 26 March 2012Available online 1 April 2012

Keywords:Coal gasifierImpinging flowHard-sphere modelDSMC methodParticle flow behavior

A 3D model of the impinging zone of a commercial scale Opposed Multi-Burner (OMB) gasifier is establishedin this article, in which the gas flow and particle motion are simulated by the Eulerian–Lagrangian approach,and the gas turbulence is calculated using the realizable k-εmodel. The particle collision is determined by theDirect Simulation Monte Carlo (DSMC) method and the modified Nanbu method, with the presumption thatthe particle is hard sphere. The model is validated with reference to the experimental result obtained on alaboratory device equipped with two opposed jets. The model reveals the concentration and mean velocityprofiles of particles in the impinging zone. It is quantitatively observed that particles move at an acceleratedspeed from the jet and then at a rapidly decelerated speed near to the central impinging zone; particles areconcentrated in the central impinging zone due to collision.

© 2012 Elsevier B.V. All rights reserved.

1. Introduction

Entrained flow coal gasification is an advanced gasification technol-ogy, which has widely found commercial applications for the produc-tion of coal-based chemicals such as methanol, ammonia, DME, andhydrogen. OMB gasifier is an entrained flowgasifier developed in China,and it has been successfully applied in several plants [1]. One of thepatented designs of OMB gasifier is to strengthen the mass and heattransfer and prolong the particle residence time via the formation of animpinging flow field. This study is focused on a model study of particleflow behavior in the impinging zone.

There are two classical methods in simulation of gas–particle flow,the Eulerian–Eulerian method which treats particles as a continuousphase and the Eulerian–Lagrangian which tracks individual particles.The latter method is used in this study to calculate the gas turbulenceand the motion of individual particle. Considering that inter-particlecollision is an important physical phenomenon in the impinging zoneof an OMB gasifier, we combine the Eulerian–Lagrangian methodwith particle collision in this study.

Particle collision is generally simulated by the soft-sphere modeland the hard-sphere model in terms of interactions betweenparticles. Cundall and Strack [2] proposed a discrete element method(DEM) in treatment of soft-sphere collision in 1979. Tsuji [3] and Xu

x: +86 021 64251312.

rights reserved.

[4] simulated a fluidized bed using the soft-sphere model. In recentyears, DEM has been used frequently by coupling with LES [5] orcommercial CFD software [6]. With respect to the hard-sphere model,inter-particle collision is treated generally as a binary and instanta-neous process and simulated by solving the conservation equation ofmomentum. Many researches verified the application of the hard-sphere model to Couette shear-flow [7], horizontal channel [8] andgas-fluidized bed [9,10]. The hard-sphere model has also widely beenused to investigate the formation and structure of bubbles andclusters in fluidized bed [11,12] and riser [13].

Direct Simulation Monte Carlo (DSMC) method is commonly usedto deal with the hard-sphere collision. In DSMC method, a particlecollision probability is assessed from a representative amount oftracked particles instead of all particles; therefore, it is advantageousin saving computing time. Tsuji [14] and Wang [15] coupled theDSMC method and the hard-sphere model to study the clusteringbehavior in a circulating fluidized bed and the gas-particle flowbehavior in a riser, respectively.

Many studies have been reported on the impinging flow. An earlystudy by Kitron [16] used a stochastic model based on Boltzmanntransport equation for description of gas–solid impinging streams.Guo [17] and Ni [18] in our research group developed a Markovchain stochastic model to predict the residence time distribution ofgas and particle in an OMB gasifier. Ni [19] further studied the flowbehavior of particle and slag in an OMB gasifier by treating particlesas liquid drops. In this work, emphasis is placed on the modeling ofinter-particle collision and interaction between solid particle andfluid associated with the gas–solid impinging flow in a commercialOMB gasifier by coupling the DSMC method with the hard-spheremodel.

Fig. 1. Collision of two hard spheres.

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2. Model description

Realistic processes in an entrained flow gasifier are very complex,which include multiphase flow, heterogeneous and homogeneousreactions, and heat transfer. For simplifying the issue, the followingassumptions are made in the modeling: (1) no chemical reactions andheat transfer are considered; (2) particle is treated as rigid hard sphere;(3) particle collision is treated as a binary and instantaneous contact;(4) effects of particle rotation on fluid field are neglected.

2.1. Fluid motion

Fluid motion is solved by the Reynolds Averaged Navier–Stokes(RANS) equations. The unknown terms of Reynolds stresses in RANSare dealt with using the eddy viscosity model based on Boussinesqhypothesis. The impingingflow is calculated using the typical Realizablek-ε model [20,21]:

∂ ρgkt� �∂t þ

∂ ρgktug;j

� �∂xi

¼ ∂∂xi

μg þμ t

σk

� � ∂kt∂xj

" #þ Gk−ρgεt þ Gb−YM

þ Sk ð1Þ

∂ ρgεt� �∂t þ

∂ ρgεtug;j

� �∂xj

¼ ∂∂xj

μg þμ t

σε

� � ∂εt∂xj

" #

þ ρgC1Sεt−ρgC2ε2t

kt þffiffiffiffiffiffiffivεt

p þ Sε ð2Þ

where σk=1.0, σε=1.2, C2=1.9, C1 ¼ max 0:43;η

ηþ 5

� �, and η is a

function of k, ε and gradient of velocity.

2.2. Particle suspension

Particle motion is solved by the hard-sphere model, in which totalparticle motion is divided into two independent motions, suspensionand collision. Suspension is determined by Newton's law expressed bythe equation of translational motion of a particle:

mpdup

dt¼ f d þ Vpg ρp−ρg

� �þ f x ð3Þ

where fd is the drag force, g represents the acceleration of gravity, and fxmeans the additional forces. Virtual mass force and pressure gradientforce are incorporated in this model. Drag force on particle is calculatedaccording to the following equation [22]:

f d ¼ 18d2pCdρgπ ug−up

��� ��� ug−up

� �ε2ε− χþ1ð Þ ð4Þ

where ε is the voidage of cell where particle is located. The dragcoefficient Cd of a particle and the equation coefficient χ are obtainedfrom the equations [22]:

Cd ¼ 0:63þ 4:8Re0:5p

!2

ð5Þ

χ ¼ 3:7−0:65exp −1:5− log10Rep� �2

2

264

375 ð6Þ

where Rep is the particle Reynolds number, which is defined as:

Rep ¼ερgdp ug−up

��� ���μg

: ð7Þ

In addition, taking into account the effect of fluid motion onparticle angular velocity, the following torque equation of a particle isadopted [23]:

T ¼ 2μgd3p ωg=2−ωp

� �1þ 0:20Re1=2p

� �20bRepb1000: ð8Þ

2.3. Particle collision

Following assumptions are made to solve the particle collision indispersed gas–particle flow: (1) inter-particle collision is assumedto be binary and instantaneous; (2) during collision process, thedistance between the centers of particles is sum of their radius fromthe negligible deformation of particles; (3) the friction betweenparticles obeys Coulomb's friction law when they keep sliding;(4) sliding occurs no longer once it stops. Fig. 1 illustrates the collisionof two hard spheres and some relevant physical variables. Post-collision velocities of particles are derived from the following impulseequations [14]:

m1 v1−v 0ð Þ1

� �¼ J ð9aÞ

m2 v2−v 0ð Þ2

� �¼ −J ð9bÞ

I1 ω1−ω 0ð Þ1

� �¼ r1n� J ð10aÞ

I2 ω2−ω 0ð Þ2

� �¼ r2n� J: ð10bÞ

The solution of Eqs. (9a), (9b), (10a) and (10b) differs dependingon whether two particles keep sliding during collision process or not.

2.4. DSMC method

Since there are an enormous amount of particles involved in oursimulation, the computation of a common hard-sphere model forparticle collision is time-consuming. The DSMC method is thereforecoupled with the hard-sphere model to solve this problem. In this

Table 1Parameters used for model validation.

Parameter Value Parameter Value

Temperature 298 (K) Mass ratio of gas–solid 1Pressure 1 (atm) Particle shape SphereGas component Air Particle density 2500 (kg·m−3)Length of nozzle 20 (mm) Particle spray angle 14°Inner diameter of nozzle 8 (mm) Time step 5×10−5 (s)Distance betweennozzles

140 (mm) Restitution coefficient 0.9

Inlet gas velocity 100 (m·s−1) Friction coefficient 0.2

Parameter Case 1 Case 2

Particle diameter 77 (μm) 33 (μm)Particle tracked ~13,400 ~18,000Inlet particle velocity 25 (m·s−1) 55 (m·s−1)

Fig. 2. Schematic diagram of two opposed jets experiment.

120 C. Li et al. / Powder Technology 225 (2012) 118–123

method, a certain number of tracked particles are taken as represen-tatives. The collision probability between tracked particles i and j in atime step is calculated by [14]:

P̂ ij ¼nNπ

di þ dj2

� �2

Gij⋅Δt��� ���: ð11Þ

Thus, the total collision probability of particle i with all otherparticles in a time step is given:

P̂ i ¼XNj¼1

P̂ ij: ð12Þ

Here, the collision probability is limited to 0 b P̂ ij b1N, so that the

total collision probability of particle i is a value between 0 and 1.The modified Nanbu method [24] is used to decide which particles

collide. In this method, every tracked particle in cell is assumed tohave the same probability to collide with particle i, so one particletaken randomly can be used as a candidate, expressed as:

k ¼ int R̂Nh i

þ 1 k≠i: ð13Þ

From Eqs. (11) and (13), the occurrence of particle collision ismade sure if the following criterion is satisfied:

R̂ >kN−P̂ ik: ð14Þ

Moreover, the particle collision only leads to a change in thevelocity of a particle but no change in the position.

3. Model validation

Model validation is conducted by comparing with the experimen-tal results obtained by our colleague [25] using two opposed jets.Fig. 2 shows the schematic diagram of the experimental apparatus

Fig. 3. Simulation domain and grid meshing (another nozzle, inlet #2, is located on theopposed side).

consisting of two opposed nozzles. The inner diameter of eithernozzle was 8 mm. The distance between two nozzles was 140 mm.Particles were conveyed by air into the nozzles. Fig. 3 shows thecalculation domain and the grid meshing with about 60,000hexahedral cells.

Table 1 lists the parameters used for the model validation. Fig. 4shows the image of particle flow taken by a high-speed camera andthe simulation results, both obtained under the same conditions (case 1in Table 1).

Fig. 5 shows the experimentally measured and simulated profilesof the particle concentration along the axis of the nozzle, in which C0is the particle concentration at the outlet of the nozzle, and L is thetotal length between the two nozzles. It is found that the simulationresult is essentially consistent with experimental result. This validatesthe model. Moreover, the particle concentration drops sharply withthe particle being away from the outlet of nozzle along x-axialdirection because of dispersion, but it increases to some degree nearto the center and appears with a smaller peak around the center.

4. Results and discussion

4.1. Snapshots of particle motion

The following part of work is targeted to model in the impingingzone of a commercial scale OMB gasifier. Fig. 6 shows the sketch ofa commercial scale OMB gasifier, which was surrounded by fouropposed burners that are horizontally mounted. The relevant param-eters used for calculation are listed in Table 2 with reference to theparameters used practically, although few of them are changedslightly for simplicity. The simulation domain is meshed into about1 160,000 hexahedral cells. No collision between particles and the

Fig. 4. Comparison of experimental image and snapshot of simulation results of particleflow. (a): experimental image; (b): simulation results.

Fig. 5. Comparison of dimensionless particle concentration profile of experimentaland simulation results. (□): experimental results; (■): simulation results. (a): case 1;(b): case 2.

Table 2Parameters used in simulation of particle flow behavior in impinging zone.

Parameter Value Parameter Value

Temperature 1523 (K) Particle diameter 120 (μm)Pressure 5.0 (MPa) Particle density 1500 (kg·m−3)Gas component H2, CO, CO2, H2O Particle spray angle 20°Gas flow rate 8.95×4 (kg·s−1) Particle tracked ~700,000Particle flow rate 3.60×4 (kg·s−1) Time step 5×10−5 (s)Inlet gas velocity 130 (m·s−1) Restitution coefficient 0.9Inlet particle velocity 15 (m·s−1) Friction coefficient 0.2Particle shape Sphere

121C. Li et al. / Powder Technology 225 (2012) 118–123

wall of reactor is involved in calculation because it can be almostneglected in this zone.

Fig. 7 shows the snapshot of particle motion on horizontal plane(i.e., XY plane) and axial plane (i.e., YZ plane), in which the resultobtained with no consideration of collision is also presented forcontrast. In both cases, particle is accelerated by the gas stream afterintroduced into the gasifier. The velocity of particle increased near tothe central region of the jet. In view of the XY plane, particles aredispersed in a larger region for the case of no collision becauseparticles pneumatically move to and fro more freely across the centralregion of the impinging zone, whereas for the case of having collision,collision strongly resists the particles motion in the central region,resulting in a concentration of particles in this region. Also, thecollision leads to a slight enhancement in particle dispersion in the jet

Fig. 6. Sketch of a commercial scale OMB gasifier and grid meshing of impinging zone.

flow. In view of the YZ plane, more particles move axially at a higherspeed after leaving the central region of the impinging zone in thecase of having collision than in the case of no collision due to theconcentrated particles caused by the particle collision in this region.

4.2. Particle concentration distribution

Particle concentration distribution is important for gasificationbecause high particle concentration readily causes the cohesion andagglomeration of char and ash particles. Fig. 8 shows the profiles ofparticle concentration along the axes of opposed burner (direction x)and gasifier (direction z). From direction x, the particle concentrationhas a maximum of 120 kg·m−3 at the center for the case of collision,which is larger than that at the outlets of the burners. A similar resultis observed for the case of no collision, but the particle concentrationat the center is smaller than that at the outlets of the burners. Fromdirection z, a sharp decrease of the particle concentration occurs asparticles are away from the cross section of the burners (z=0).

4.3. Particle velocity

Fig. 9 shows the mean horizontal velocity of particle along the axisof burner (direction x) and the mean axial velocity along the axis ofgasifier (direction z). In both directions of x and z, only slightdifferences occur between the case of no collision and the case ofhaving collision. From direction x, it is clearly seen that the meanhorizontal velocity of particles increases from 40 m·s−1 at the outletsof the burners to about 100 m·s−1, and then sharply decreases nearto a central region because of the drag force and particle collision.Comparison of the gas velocity with the mean horizontal velocity ofparticle exhibits a reduction followed by an increase in theirdifference with the particles approaching the center. As an advantageof impinging flow, the increment of relative velocity between gas andsolid phases enhances inter-phase mass and heat transfer in centralregion of impinging zone. From direction z, both the gas velocity and

Fig. 7. Snapshot of particle motion in horizontal plane (XY plane) and axial plane (YZplane). (a): no collision; (b): with collision.

Fig. 8. Particle concentration distribution profiles. (—): no collision; (―): with collision.(a): along the axis of burner; (b): along the axis of gasifier.

Fig. 9.Mean particle velocity profiles. (■): particle velocity (no collision); (□): particlevelocity (with collision); (—): gas velocity (no collision); (―): gas velocity (withcollision). (a): mean horizontal velocity along axis of burner; (b): mean axial velocityalong axis of gasifier.

122 C. Li et al. / Powder Technology 225 (2012) 118–123

the mean axial velocity of particle at the center (z=0) are about zero;with the particle being distant from the center, the gas velocitybecomes larger than the mean axial velocity of the particle.

5. Conclusion

A 3D model of the impinging zone of a commercial scale OMBgasifier has been established and validated to study particle flowbehavior. The following conclusions have been drawn: (1) inter-particle collision strongly resists the particles motion, concentratesparticles in the central region of impinging zone and slightlyenhances particle dispersion in the jet flow; (2) in the center ofimpinging zone, collision increases the chance of particle cohesionand agglomeration by resulting a high particle concentration region,in which, particle concentration is larger than that at the outlets ofburners; (3) high relative velocity between gas–solid phases causedby the rapid deceleration of particles is observed near the center ofimpinging zone, which improves the performance of gasifier in termsof heat and mass transfer.

NomenclatureCd drag coefficientdp diameter of particlee coefficient of restitutionfd vector of dragfx total force of other forcesg vector of gravitational acceleration

I1, I2 moment of inertia of particles 1 and 2J vector of collision impulsek turbulence kinetic energy; index of candidate particlem1, m2 mass of particles 1 and 2mp mass of particlen unit normal vector of contact point of particle collisionn number density of real particle in cellN number of track particle in cellp pressure of gas phaseP̂ ij collision probability of particles i and jP̂ i total probability of particle i and other particles in a single

time stepr1, r2 radius of particles 1 and 2Rep Reynolds number of particlet unit tangential vector of contact point of particle collisionΔt time step of DSMC methodT vector of torque of particleup vector of particle velocityug vector of gas velocityv1, v2 velocity vector of particles 1 and 2 after collisionv1(0), v2(0) velocity vector of particles 1 and 2 before collision

Greek lettersχ equation coefficient of drag forceε voidage; dissipation rate of turbulence kinetic energyμ viscosity of gas

123C. Li et al. / Powder Technology 225 (2012) 118–123

ρp density of particleρg density of gasωg vector of angular velocity of gasωp vector of angular velocity of particleω1, ω2 angular velocity vector of particles 1 and 2 after collisionω1

(0), ω2(0) angular velocity vector of particles 1 and 2 before collision

ξ coefficient of friction

Subscriptg gas phasep particle phasei, j index of particle, index of component of gas velocity

Acknowledgments

Thiswork is supported by the National High Technology Research andDevelopment Program of China (no. 2008AA050301), the National BasicResearch Program of China (no. 2010CB227000) and the FundamentalResearch Funds for the Ministry of Education (no. WB1014037). Thanksare due to our colleagues Prof. Haifeng Liu and Dr. Zhigang Sun forproviding experimental data in model validation. We also wish toacknowledge Prof. Jie Wang for his revision of this paper.

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