Analysis of four Monte Carlo methods for the solution of population balances in dispersed systems

H. Zhao, A. Maisels, T. Matsoukas, C. Zheng

Research output: Contribution to journalArticlepeer-review

95 Scopus citations

Abstract

Monte Carlo (MC) constitutes an important class of methods for the numerical solution of the general dynamic equation (GDE) in particulate systems. We compare four such methods in a series of seven test cases that cover typical particulate mechanisms. The four MC methods studied are: time-driven direct simulation Monte Carlo (DSMC), stepwise constant-volume Monte Carlo, constant number Monte Carlo, and multi-Monte Carlo (MMC) method. These MC's are introduced briefly and applied numerically to simulate pure coagulation, breakage, condensation/evaporation (surface growth/dissolution), nucleation, and settling (deposition). We find that when run with comparable number of particles, all methods compute the size distribution within comparable levels of error. Because each method uses different approaches for advancing time, a wider margin of error is observed in the time evolution of the number and mass concentration, with event-driven methods generally providing better accuracy than time-driven methods. The computational cost depends on algorithmic details but generally, event-driven methods perform faster than time-driven methods. Overall, very good accuracy can be achieved using reasonably small numbers of simulation particles, O(103), requiring computational times of the order 102-103 s on a typical desktop computer.

Original languageEnglish (US)
Pages (from-to)38-50
Number of pages13
JournalPowder Technology
Volume173
Issue number1
DOIs
StatePublished - Apr 10 2007

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)

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