An efficient method for spatiotemporally resolved aerosol flow modeling: Discrete migration and GPU acceleration

• Published in: AIChE journal 2023-09, Vol.69 (9), p.n/a
• Main Authors: Shang, Cheng, Su, Zhijing, He, Song, Xu, Zuwei, Kruis, Frank Einar, Zhao, Haibo
• Format: Article
• Language: English
• Subjects: CFD‐PBMC simulation; Computational fluid dynamics; Computer applications; Computing costs; Convection; differentially weighted Monte Carlo; Fluid dynamics; GPU parallel computation; Graphics processing units; Hydrodynamics; Mathematical models; Monte Carlo simulation; Parallel processing; particle migration model; Peripheral blood mononuclear cells; population balance; Population balance models; Random walk
• ISSN: 0001-1541; 1547-5905
• DOI: 10.1002/aic.18123

Describing spatiotemporal evolution and characteristics of dispersed systems using the population balance equation (PBE), examples including sectional and moment methods are fraught with numerous issues. Hence, this study develops an accurate method by combining computational fluid dynamics and population balance‐Monte Carlo method (CFD‐PBMC) with a moderate computational cost. An efficient sub‐model for particle migration was proposed to simulate the convection and diffusion processes of particulate flows. A graphics processing unit (GPU)‐based parallel computation was performed to accelerate the high‐dimensional CFD‐PBMC. Several classical cases with analytical or benchmark solutions were simulated, and a comprehensive comparison was made using the classical weighted random walk method. Good agreements were obtained, except in the case of radial migration, the reasons for which are explained in detail. The measured speedups on the GPU showed a factor of ~450 for pure migration and ~50 for the CFD‐PBMC method when compared with a standard high‐performance computer.