US EPA

2641053 

Journal Article 

Fast Monte Carlo simulation for particle coagulation in population balance 

Xu, Z; Zhao, H; Zheng, C 

2014 

Yes 

Journal of Aerosol Science
ISSN: 0021-8502
EISSN: 1879-1964 

74 

11-25 

10.1016/j.jaerosci.2014.03.006 

WOS:000337869100002 

The Monte Carlo (MC) method for population balance modeling (PBM) has become increasingly popular because the discrete and stochastic nature of the MC method is especially suited for particle dynamics. However, for the two-particle events (typically, particle coagulation), the double looping over all simulation particles is required in normal MC methods, and the computational cost is O(N-s(2)), where N-s is the simulation particle number. This paper proposes a fast random simulation scheme based on the differentially-weighted Monte Carlo (DWMC) method. The majorant of coagulation kernel was introduced to estimate the maximum coagulation rate by a single looping over all particles rather than the double looping. The acceptance-rejection process then proceeded to select successful coagulation particle pairs randomly, and meanwhile the waiting time (time-step) for a coagulation event was estimated by summing the coagulation kernels of rejected and accepted particle pairs. In such a way, the double looping is avoided and computational efficiency is greatly improved as expected. Five coagulation cases for which analytical solutions or benchmark solutions exist were simulated by the fast and normal DWMC, respectively. It is found the CPU time required is orders of magnitude lower and only increases linearly with N-s; at the same time the computational accuracy is guaranteed very favorably. (C) 2014 Elsevier Ltd. All rights reserved. 

Population balance modeling; Particle coagulation; Stochastic simulation; Differentially weighting scheme; Particle size distribution