Simulation of Solid-Liquid Cascade Filtration Based on CFD-DEM
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摘要: 采用计算流体力学(CFD)和离散单元法(DEM)耦合的方法，在不同滤层结构的三维随机堆积颗粒层过滤器内进行固液分级过滤的数值模拟研究。实验结果表明，过滤效率的模拟计算值与实验值吻合良好，压降值的偏差在Ergun方程允许误差范围内。过滤器的容垢能力由模型计算的颗粒沉积均匀度表示，并拟合得到沉积均匀度的关联式。颗粒沉积分布的模拟结果显示：单层细滤料过滤器的颗粒沉积主要发生在近入口处，容垢能力较低；分级过滤器的细滤料层保证了高过滤效率，粗滤料层则提供了较大的容垢能力。Abstract: A three-dimensional model for a random packed bed filter was established by coupling computational fluid dynamics (CFD) and discrete element method (DEM). To ensure more accurate simulation results can be obtained, the interactions of liquid-solid, particle-granule and particle-particle were taken into consideration. The filtration performance including filtration efficiency, pressure drop and impurity holding capacity were carefully analyzed, and particle deposition distribution and morphology were also numerically investigated. The simulation results of filtration efficiency have a good agreement with the experimental results. The deviation of the pressure drop is within the allowable error range of the Ergun equation. The impurity holding capacity is represented by the deposition uniformity obtained by simulation results, which increases with the superficial velocity. Correlation of deposition uniformity for granular bed filters is presented and it has good prediction accuracy. The results show that cascade filtration has both a high filtration efficiency and a low pressure drop by combining deep bed filtration and surface filtration. The quality factor of the cascade filter is greater than that of a single-layer filter. The simulation analysis of particle deposition morphology and distribution shows that particles mainly deposit on the surface of single-layer filter packed with fine granules, resulting in its small holding capacity. As for the cascade filter, the fine granular layer ensures high filtration efficiency while coarse granular layer provides large impurity holding capacity.
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图 6 (a)初始压降的实验值和计算值比较；(b)不同床层深度下的初始压降
Figure 6. (a) Comparison of initial pressure drop between experiment and simulation; (b) Initial pressure drop under different bed depths
图 7 (a)过滤效率的实验值和模拟值比较；(b)不同床层深度下的过滤效率模拟值
Figure 7. (a) Comparison of filtration efficiency between experiment and simulation; (b) Simulation results of filtration efficiency under different bed depths
图 9 细滤料层表面的颗粒沉积形貌
Figure 9. Deposition morphology on the surface of fine granular layer
图 10 不同过滤器同一纵截面的颗粒沉积形貌
Figure 10. Particle deposition morphology in the same longitudinal section of different filters
图 11 颗粒的沉积分布 (a)沉积分数；(b)沉积均匀度
Figure 11. Particle deposition distribution (a) Deposited fraction; (b) Deposition uniformity
图 12 沉积均匀度的预测结果和计算结果的对比
Figure 12. Comparison of deposition uniformity between predicted and calculated results
表 1 模拟物性参数
Table 1. Physical parameters in the simulation
Density/
(kg·m−3)Poisson’s ratio Shear modulus/Pa Particle (granule) 3200 0.25 1.0×108 Wall 1500 0.25 1.1×109 Restitution coefficient Static friction coefficient Rolling friction coefficient Particle to particle (granule) 0.5 0.154 0.05 Particle to wall 0.3 0.154 0.01 
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