GPU accelerated MFiX-DEM simulations of granular and multiphase flows

作     者：Liqiang Lu Liqiang Lu

作者机构：National Energy Technology LaboratoryMorgantownWV 26507United States Leidos Research Support TeamMorgantownWV 26506United States 

出 版 物：《Particuology》 (颗粒学报（英文版）)

年 卷 期：2022年第20卷第3期

页      面：14-24页

核心收录：

学科分类：080704[工学-流体机械及工程] 080103[工学-流体力学] 08[工学] 0807[工学-动力工程及工程热物理] 0801[工学-力学（可授工学、理学学位）] 

基　　金：U.S. Department of Energy, USDOE National Energy Technology Laboratory, NETL 

主　　题：GPU MFIX DEM Drag Fluidization 

摘      要：In this research,a Graphical Processing Unit(GPU)accelerated Discrete Element Method(DEM)code was developed and coupled with the Computational Fluid Dynamic(CFD)software MFiX to simulate granular and multiphase flows with heat transfers and chemical *** Fortran-based CFD solver was coupled with the CUDA/C++based DEM solver through inter-process *** speedup to the CPU version of MFiX-DEM is about 130-243 folds in the simulation of particle *** fluidized bed simulations,the DEM computation time is reduced from 91%to 17%with a speedup of 78 *** simulation of Geldart A particle fluidization revealed a similar level of importance of both fluid and particle *** filtered drag derived from the two-fluid model is suitable for Euler-Lagrangian simulations with both fluid and particle *** overcorrects the influence of sub-grid structures if used for simulations with only fluid coarse-graining.