A modified CFD-DEM method for accurate prediction of the minimum fluidization velocity

Xuan He, Yaxiong Yu, Zhouzun Xie, Qiang Zhou
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Abstract

Monodisperse fluidized bed experiments have been carried out on 13 kinds of particles with different particle sizes in a cylindrical fluidized bed. The accuracy of nine commonly used monodisperse drag models, including the Gidsapow, BVK, and Zhou–Fan models is verified. It is found that the Zhou–Fan model is the most accurate at low and moderate values of the particle Reynolds number. It is found that with the traditional computational fluid dynamics–discrete element method (CFD-DEM) method it is difficult to obtain an accurate minimum fluidization velocity owing to difficulty in obtaining an accurate value of the minimum fluidization solid volume fraction. A modified method is proposed to increase the accuracy of prediction of the minimum fluidized solid volume fraction by using a virtual particle size in the calculation of the particle collision process. The effectiveness of the modified method is verified by comparing the CFD-DEM simulation results with experimental results for Geldart-D particles. The relative error of the minimum fluidization velocity is found to be reduced from 24.6% to 2%.
精确预测最小流化速度的改进型 CFD-DEM 方法
对圆柱流化床中不同粒径的 13 种颗粒进行了单分散流化床实验。验证了包括 Gidsapow、BVK 和 Zhou-Fan 模型在内的九种常用单分散阻力模型的准确性。结果发现,在颗粒雷诺数为中低值时,Zhou-Fan 模型最为精确。研究发现,采用传统的计算流体力学-离散元方法(CFD-DEM),由于难以获得最小流化固体体积分数的精确值,因此很难获得精确的最小流化速度。为了提高最小流化固体体积分数预测的准确性,提出了一种改进方法,即在计算颗粒碰撞过程中使用虚拟颗粒尺寸。通过比较 CFD-DEM 模拟结果和 Geldart-D 颗粒的实验结果,验证了改进方法的有效性。结果发现,最小流化速度的相对误差从 24.6% 降至 2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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