期刊
JOURNAL OF COMPUTATIONAL PHYSICS
卷 340, 期 -, 页码 276-296出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2017.03.041
关键词
Simulation; Population balance; Coagulation; Nucleation; Monte Carlo; GPU computing
资金
- Deutsche Forschungsgemeinschaft (DFG) [SPP 1679 (KR 1723/15-2)]
Monte Carlo simulations based on weighted simulation particles can solve a variety of population balance problems and allow thus to formulate a solution-framework for many chemical engineering processes. This study presents a novel concept for the calculation of coagulation rates of weighted Monte Carlo particles by introducing a family of transformations to non-weighted Monte Carlo particles. The tuning of the accuracy (named 'stochastic resolution' in this paper) of those transformations allows the construction of a constant-number coagulation scheme. Furthermore, a parallel algorithm for the inclusion of newly formed Monte Carlo particles due to nucleation is presented in the scope of a constant-number scheme: the low-weight merging. This technique is found to create significantly less statistical simulation noise than the conventional technique (named 'random removal' in this paper). Both concepts are combined into a single GPU-based simulation method which is validated by comparison with the discrete-sectional simulation technique. Two test models describing a constant-rate nucleation coupled to a simultaneous coagulation in 1) the free-molecular regime or 2) the continuum regime are simulated for this purpose. (C) 2017 Elsevier Inc. All rights reserved.
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