GPU accelerated MFiX-DEM simulations of granular and multiphase flows

被引:22
|
作者
Lu, Liqiang [1 ,2 ]
机构
[1] Nat Energy Technol Lab, Morgantown, WV 26507 USA
[2] Leidos Res Support Team, Morgantown, WV 26506 USA
来源
PARTICUOLOGY | 2022年 / 62卷
关键词
GPU; MFIX; DEM; Drag; Fluidization; DISCRETE PARTICLE METHODS; SCALE SIMULATION; FLUIDIZED-BEDS; VALIDATION; MODELS; SIZE;
D O I
10.1016/j.partic.2021.08.001
中图分类号
TQ [化学工业];
学科分类号
0817 ;
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 reactions. The Fortran-based CFD solver was coupled with the CUDA/C++ based DEM solver through inter-process pipes. The speedup to the CPU version of MFiX-DEM is about 130-243 folds in the simulation of particle packings. In fluidized bed simulations, the DEM computation time is reduced from 91% to 17% with a speedup of 78 folds. The simulation of Geldart A particle fluidization revealed a similar level of importance of both fluid and particle coarse-graining. The filtered drag derived from the two-fluid model is suitable for EulerLagrangian simulations with both fluid and particle coarse-graining. It overcorrects the influence of sub grid structures if used for simulations with only fluid coarse-graining. (c) 2021 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
引用
收藏
页码:14 / 24
页数:11
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