The gas-solid flows in a 2-dimensional downer were simulated using a CFD-DEM method. The predicted macro-scale flow structure had good agreement with the experiments. The distinct clustering phenomena at meso-scale were revealed throughout the downer. Influences of the collision properties of the wall and the particles on the hydrodynamics in downer were investigated

Cheng, Yi

Ding, Yulong

Jin, Yong

Zhao, Yongzhi

English

Engineering Conferences International

Refereed ProceedingsThe 12th International Conference onFluidization - New Horizons in FluidizationEngineeringEngineering Conferences International Year 2007Understanding the Hydrodynamics in a2-Dimensional Downer by CFD-DEMSimulationYongzhi Zhao∗ Yi Cheng†Yulong Ding‡ Yong Jin∗∗∗Tsinghua University†Tsinghua University, yicheng@tsinghua.edu.cn‡∗∗Tsinghua UniversityThis paper is posted at ECI Digital Archives.http://dc.engconfintl.org/fluidization xii/105FLUIDIZATION XII  855    UNDERSTANDING THE HYDRODYNAMICS IN A 2-DIMENSIONAL DOWNER BY CFD-DEM SIMULATION  Y.Z. Zhao, Y. Cheng*, Y.L. Ding, Y. Jin Department of Chemical Engineering, Tsinghua University, Beijing 100084, China *F: 86-10-6277-2051; E: yicheng@mail.tsinghua.edu.cn ABSTRACT The gas-solid flows in a 2-dimensional downer were simulated using a CFD-DEM method. The predicted macro-scale flow structure had good agreement with the experiments. The distinct clustering phenomena at meso-scale were revealed throughout the downer. Influences of the collision properties of the wall and the particles on the hydrodynamics in downer were investigated.  INTRODUCTION Downer has drawn much attention in both academia and industry for its unique features such as a uniform flow structure and a plug-flow behavior for gas and solids phases, which indicates a great potential as the next-generation reactor technique for ultra-short contact processes. A wealth of experimental studies on the downer has been reported in the literature, while few papers were published on CFD modeling and simulations. In particular, a comprehensive understanding on the clustering phenomena in the downer has not been reached using a theoretical method. Cheng et al. (1) have applied an Eulerian-Eulerian model to simulate the hydrodynamics in the downer. However, Eulerian model cannot describe the detailed interaction between phases and between particles at micro-scale. In recent years, Eulerian-Lagrangian model, the so-called CFD-DEM method pioneered by Tsuji et al. (2), has been widely applied in the simulation of gas-solid flows, where the particles are traced individually by solving Newton’s equations of motion, while the gas phase is treated as a continuum that is coupled to the motion of particles via an interphase interaction term. The advantage of the CFD-DEM simulation is that the micro-dynamic behavior of granular materials at the individual particle level can be modeled with clear physical meaning.  In this work, the CFD-DEM coupling method is used to study the hydrodynamics in a 2-dimensional downer with the width of 10 cm and the height of 10 m to ensure the 1Zhao et al.: CFD-DEM Simulations of a DownerPublished by ECI Digital Archives, 2007ZHAO et al.  856two-phase flow reaching fully developed. The DEM code has been successfully incorporated with the commercial CFD package of FLUENT 6.1. The macro-scale flow structure and the meso-scale clustering phenomena are disclosed by the simulation results. Influences of the properties of the wall and the particles on the hydrodynamics in downer are to be discussed. MATHEMATICAL MODEL The particle movement is described by the Newton equation of motion which includes the effects of gravitational force, contact force, fluid drag force, and buoyant force. The equations of transitional and rotational motions can be written as dc d bm mdt= + + +V g F F F             (1) dcI dt=Tω                 (2) The motion of fluid is modeled by the equation of continuity and the equation of momentum conservation, which are given by ( )0jjut xεε ∂∂ + =∂ ∂               (3) ( ) ( )i j ji if f f sj i j j iu u uu upt x x x x xεερ ρ εµ ∂  ∂∂ ∂∂ ∂+ = − + + +   ∂ ∂ ∂ ∂ ∂ ∂   F     (4) Di Felice drag model (3) is used to characterize the gas-solid interaction. The details about the contact force models, coupling between discrete and continuum models, and numerical schemes can be found elsewhere (Zhao et al. (4)). The simulation parameters are given in Table 1. A total of three cases are simulated to explore the influence of the collision properties between particles and the wall. Case 1 is the reference case with more realistic particle properties. The detailed differences with the other two cases Table 1 Simulation parameters Gas properties Density/kg·m-3 1.225 Viscosity/N·s·m-2 1.72×10-5 Particle properties Shape Spherical Diameter/mm 0.5 Density/kg·m-3 950 Simulation parameters Number of particles About 70,000 DEM time step/s 5×10-6 Total simulation time/s 5 Gas inlet velocity/m·s-1 4.0 Solids flux/kg·m-2·s-1 50 Width/m ×Height/m 0.1×10 CFD Mesh 20(W)×500(H)2The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 105 [2007]http://dc.engconfintl.org/fluidization_xii/105FLUIDIZATION XII  857are shown in Table 2. Case 2 and Case 3 are used to study the influence of wall and particles properties respectively. Table 2 Simulation parameters of three cases Parameters Case 1  Case 2 Case 3 Particle-particle collisions    Normal coefficient of restitution Coefficient of sliding friction 0.95 0.1 0.95 0.1 1.0 0.0 Particle-wall collisions    Normal coefficient of restitution Coefficient of sliding friction 0.95 0.1 0.9 0.3 1.0 0.0 In the continuum model, the no-slip boundary condition applies to the bed walls and zero diffusion flux condition to the bottom exit. At the top of the bed, the gas and the particles are introduced. The assistant gas (u = 1 m/s) carrying particles (Gs = 50 kg/m2s) falls through 5 tubes, and the main gas (u = 7 m/s) flows into the bed through the space between the tubes. Case 1 Case 2 Case 3      Fig. 1 Snapshots of flowpatterns (t = 2.5 s)   Case 1 0-1m 1-2m 2-3m 3-4m 4-5m 5-6m 6-7m 7-8m 8-9m 9-10mFig. 2 Snapshots of Case 1 at simulation time t = 2.5 s  RESULTS AND DISCUSSION 3Zhao et al.: FD-DEM Simulations of a DownerPublished by ECI igital Archives, 2007ZHAO et al.  858A total of 5 s simulation was performed for each of the three cases. The particles are introduced from the tube inlet at the top of the bed, and then move downward. After about 2.0 seconds, the particles run out of the downer and the gas-solid flow becomes to be steady. Fig. 1 shows the snapshots of flow patterns of three cases at simulation time t = 2.5 s. It can be seen that many clusters exist in the reactors, and the number of clusters and their sizes vary along the downer. The cluster size increases observably as the increase of the bed length, which agrees well with the investigations by Lu et al. (5). Some researchers (e.g. Krol et al., (6); Lu et al., (5)) also observed particle clusters in downer by different measuring techniques. However, the temporal-spatial dynamics inside the bed cannot be obtained due to the limitation in experiments. Fig. 2 provides a more detailed distribution of solid particles in the downer. In the section 0-3 m of the bed, the particles are dispersed uniformly and no cluster exists. In the section 3-4 m clusters start forming, and in the section 4-6 m the size and the number of clusters all increases along the bed. In the rest section 6-10 m, the size of clusters still increases, but the number of clusters is obviously reduced. The variation of the number of clusters along the bed also agrees with the experiments (Lu et al., (5)). The shapes of clusters are anomalous and often in the form of floc structure with loosely collected particles. At the lower section of the downer, the occurrence probability of clusters near the bed wall is higher than that in the bed center, and the size of clusters near the wall is also larger than that in the center.      (a) 1.8-2.0m    (b) 3.8-4.0m    (c) 5.8-6.0m     (d) 7.8-8.0m  (e) 9.8-10.0m Fig. 3 Snapshots of the local gas velocity and particle structure in different parts of the downer (Case 1) at simulation time t = 2.5 s Fig. 3 shows the snapshots of the local gas velocity and particle structure in different parts of the downer (Case 1) at simulation time t = 2.5 s. It can be seen that the flow structures of gas and particles are different at different positions. At the higher part of the bed, shown in Fig. 3(a), the flow of gas is generally uniform and particles are dispersed uniformly too. At the middle section shown in Figs. 3(b) and (c), particle cluster appears and the flow structure of the gas changes to be non-uniform. The 4The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 105 [2007]http://dc.engconfintl.org/fluidization_xii/105FLUIDIZATION XII  859reason is that the velocity difference between particles and gas increases gradually along the bed caused by gravity. The large velocity difference makes gas-solid flow unbalanced. Particles turn to moving together to be clusters and the flow of the gas is disturbed by the particle clusters. Further downwards, the particles move faster in the lower part of the downer. The size of clusters increases and the gas flow is influenced by the existence of clusters to a greater extent, shown in Figs. 3(d) and (e). The gas velocity is larger near the cluster due to the larger drag forces between phases. As the cluster size increases to its limit, the inter-collisions between particles and the drag forces from the gas make clusters breaking-up.  Fig. 4 shows the influence of the particle properties on the clustering phenomenon. It can be seen that the ideal particles used in Case 3 disperse much faster near the entrance because of the fully elastic collisions between particles. And the clusters are more loosely packed by the ideal particles. Lateral profiles of the solids fraction at 10 different axial positions for the three cases are shown in Fig. 5. The averaging period is from 2.5s to 5.0s. The distributor affected region below the entrance of the bed can be clearly seen. At the location H = 1.5 m, the lateral solid fraction profiles of all cases change to be very flat, indicating the weakened influence of distributor on the hydrodynamics. However, as particles move downwards, clusters start forming and the particles begin to move towards the wall. At the location H = 4.5 m, the lateral solid fraction profiles become non-uniform. A dense ring occurs near the wall. The results agree well with the observations made by many investigators (e.g. Bai et al., (7); Lehner and Wirth, (8)).  Fig. 6 shows the axial profiles of solids fraction, gas and particle velocities for three cases. It can be seen that the cross-sectional averaged solids fraction profile firstly decreases rapidly in the higher region (0~2 m) of the bed, then decreases slowly and finally being constant. The gas velocity changes little along the downer, while the  Case 1    Case 3    Case 1 Case 3   (a) Near the entrance  (b) Near the outlet Fig. 4 Influence of the particle properties on the clustering phenomenon at t = 2.5 s 5Zhao et al.: CFD-DEM Simulations of a DownerPublished by ECI Digital Archives, 2007ZHAO et al.  860particles experience clear acceleration process due to the drag force at the beginning and the gravity force all along. The simulation results agree well with the experimental results (e.g. Zhang et al., (9); Zhang et al., (10)). In order to validate if the flow reaches the fully developed state, the standard deviation (SD) of particle velocity indicating the lateral variation of the local velocities is studied. At H = 0 m the SD values are very high, which shows the strong effect by the distributor design below the entrance. Then, the SD values decrease rapidly. Since the clusters start forming and the flow becomes non-uniform in the middle region (2~8 m), the SD increases almost linearly. In the lower region (8~10 m), the SD profiles change to be flat. H=0.5 mH=1.5 mH=2.5 mH=3.5 mH=4.5 mH=9.5 mH=8.5 mH=7.5 mH=6.5 mH=5.5 mSolids fraction0.0000.0050.0100.0150.0200.0000.0050.0100.0150.0000.0050.0100.0150.0000.0050.0100.0150.0000.0050.0100.0150.0000.0050.0100.0150.0000.0050.0100.0150.0000.0050.0100.0150.0000.0050.0100.0150.00 0.02 0.04 0.06 0.08 0.100.0000.0050.0100.015                    0.00 0.02 0.04 0.06 0.08 0.10                    0.00 0.02 0.04 0.06 0.08 0.10                    x/m Fig. 5 Lateral profiles of solids fraction along the downer of three cases. As shown above, the flow reaches the fully developed state in the lower region of the downer. In order to get the more meaningful lateral profiles of solids fraction and particle velocity corresponding to fully developed region, the space-time averaging of 6The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 105 [2007]http://dc.engconfintl.org/fluidization_xii/105FLUIDIZATION XII  861solid fractions and particle velocities is carried out in the lower region (8~10 m) of downer. It can be seen from Fig. 7 that more particles appear near the wall so that a dense ring of particles form, which accordingly result in higher particle velocities at the corresponding place. The effect of the wall properties in downer is also shown in Fig. 7. Under the simulation conditions, the change of wall properties (Case 2) has little influence on the flow structure in downer. But the effect of particle properties on the flow is greater (Case 3). The hydrodynamics in downer with particles of no friction and no collision energy loss are more uniform. 0 2 4 6 8 100.00.30.60.9 Standard deviationH/m Case 1 Case 2 Case 32.04.06.0  Velocity/m⋅s-1GasParticle0.010.020.03 Solids fraction Fig. 6 Axial profiles of solids fraction,gas and particle velocities andstandard deviation of particle velocity.   0.00 0.02 0.04 0.06 0.08 0.105.25.66.06.46.8 Case 1 Case 2 Case 3Particle velocity/m⋅s-1x/m0.0000.0050.0100.0150.020 Solids fraction Fig. 7 Lateral profiles of solids fraction,particle velocity in fully developed region  CONCLUSIONS The CFD-DEM simulations revealed the distinct clustering phenomena in downer.  The clusters start to form in the transition region instead of the entrance region with denser particle concentration. With the flow development, the clusters grow in size and increase in number. Particles inside each cluster are loosely collected, flowing in the same direction as the bulk flow. The lateral distribution of solids fraction in the fully developed region is non-uniform, with a denser ring near the wall. The ideally elastic particles with no friction during collisions disperse very rapidly and uniformly at the entrance.  ACKNOWLEDGEMENT This research is financially supported by NSFC (No. 20306012), Chinese Ministry of Education (FANEDD, No. 200245), and China Postdoctoral Science Foundation (2005038061). 7Zhao et al.: CFD-DEM Simulations of a DownerPublished by ECI Digital Archives, 2007ZHAO et al.  862NOTATION CFD computational fluid dynamics DEM discrete element method Fb  buoyant force, N Fc  contact force, N Fd  drag force, N Fs source term due to fluid drag force, N/m3 g  acceleration of gravity, m/s2 H distance from the downer entrance, m m  Mass of particle, kg p  pressure, Pa t  time, s Tc  contact Torque, N·m ui, uj, u gas velocity, m/s V  particle velocity, m/s xi, xj coordinates, m  Greeks ε  void fraction, dimensionless µf  gas viscosity, kg/m·s ρf  gas density, kg/m3 ω particle angular velocity, rad/s  Subscripts f  fluid phaseREFERENCES 1. Cheng, Y., Guo, Y., Wei, F., Jin, Y., Lin, W., 1999. Modeling the hydrodynamics of downer reactors based on kinetic theory. Chemical Engineering Science, 54, 2019-2027. 2. Tsuji, Y., Kawaguchi, T., Tanaka, T., 1993. Discrete particle simulation of two-dimensional fluidized bed. Powder Technology, 77, 79-87. 3. Di Felice, R., 1994. The voidage function for fluid-particle interaction systems. International Journal of Multiphase Flow, 20, 153-159. 4. Zhao, Y., Cheng, Y., Jin, Y., 2007. CFD-DEM simulation of clustering phenomena in riser and downer. Journal of Chemical Industry and Engineering (China), 58, (in press). 5. Lu, X., Li, S., Du, L., Yao, J., Lin, W., Li, H., 2005. Flow structures in the downer circulation fluidized bed. Chemical Engineering Journal, 112, 23-31. 6. Krol, S., Pekediz, A., De Lasa, H., 2000. Particle clustering in down flow reactors. Powder Technology, 108, 6-20. 7. Bai, D.R., Jin, Y., Yu, Z.Q., Gan, N.J., 1991. Radial profiles of local solid concentration and velocity in a concurrent downflow fast fluidized bed. In: P. Basu, M. Horio, M. Hasatani (Eds.), Circulating Fluidized Bed Technology III. Pergamon Press, Toronto, pp. 157-162. 8. Lehner, P., Wirth, K.E., 1999. Characterization of the flow pattern in a downer reactor. Chemical Engineering Science, 54, 5471-5483. 9. Zhang, H., Zhu, J-X., 1999. Hydrodynamics in downflow fluidized beds: (1): solids concentration profiles and pressure gradient distributions. Chemical Engineering Science, 54, 5461-5470. 10. Zhang, H., Zhu, J-X., 2000. Hydrodynamics in downflow fluidized beds: (2). Particle velocity and solids flux profiles. Chemical Engineering Science, 55, 4367-4377. 8The 12th International Conference on Fluidization - New Horizons in Fluidization Engineering, Art. 105 [2007]http://dc.engconfintl.org/fluidization_xii/105

Understanding the Hydrodynamics in a 2-Dimensional Downer by CFD-DEM Simulation

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Understanding the Hydrodynamics in a 2-Dimensional Downer by CFD-DEM Simulation

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