Abstract Residence time distribution of particles is a critical parameter for proper design of gas-solid fluidized beds, especially in many non-catalytic solid conversion processes where it is highly desirable to match the residence time of a particle and its complete conversion time to achieve the synchronized conversion of particles of different sizes. However, the requisite of considering particle polydispersity and the long residence time of particles required by reaction kinetics together pose a great challenge to the computational fluid dynamics study of such systems. To this end, a GPU-based, massively parallel coarse-grained CFD-DEM method-the EMMS-DPM method (Lu et al., 2014) was extended to simulate the residence time distribution of polydisperse particles in a continuously operated multiple-chamber fluidized bed with a calculation of physical time of up to one hour. It was shown that the experimentally measured pressure drop of the bed or the solid holdup can be predicted reasonably well by the ad hoc drag models of non-spherical and polydisperse particles proposed in present study; the residence time distribution of particles of whole system can also be predicted correctly; and finally, the ratio of the mean residence time of coarse particles to that of fine particles is about three, which is insufficient to achieve the synchronized conversion of particles of different sizes according to an ideally theoretical analysis, great effort is needed to get a better match between the residence time and the compete conversion time of particles.

中文翻译：

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连续运行的多室流化床中多分散颗粒停留时间分布的长时间粗粒 CFD-DEM 模拟

摘要 颗粒的停留时间分布是正确设计气固流化床的关键参数，特别是在许多非催化固体转化过程中，非常需要颗粒的停留时间与其完全转化时间相匹配以实现不同尺寸颗粒的同步转换。然而，同时考虑颗粒多分散性和反应动力学所需的颗粒长停留时间的必要性对此类系统的计算流体动力学研究提出了巨大挑战。为此，一种基于 GPU 的、大规模并行的粗粒度 CFD-DEM 方法——EMMS-DPM 方法（Lu 等人，2014) 扩展到模拟多分散颗粒在连续运行的多室流化床中的停留时间分布，物理时间计算长达一小时。结果表明，通过本研究中提出的非球形和多分散颗粒的特别阻力模型，可以很好地预测床的实验测量压降或固体滞留量；整个系统中颗粒的停留时间分布也能准确预测；最后，粗颗粒的平均停留时间与细颗粒的平均停留时间之比约为3，根据理想的理论分析，这不足以实现不同尺寸颗粒的同步转换，