4.6 Article

A new weighted fraction Monte Carlo method for particle coagulation

Journal

Publisher

EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/HFF-07-2020-0449

Keywords

Fraction function; General dynamic equation; Multi-Monte Carlo method; Particle coagulation; Weighted fraction Monte Carlo method

Funding

  1. Research Grants Council of the Hong Kong Special Administrative Region, China [PolyU 152663/16E]
  2. Central Research Grant [B-Q54U]
  3. Department of Mechanical Engineering of The Hong Kong Polytechnic University

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This study introduces a newly developed WFMC method for investigating the aerosol dynamics of the particle coagulation process, which significantly reduces critical stochastic error and extends the particle size distribution for larger sizes.
Purpose The purpose of this study is to investigate the aerosol dynamics of the particle coagulation process using a newly developed weighted fraction Monte Carlo (WFMC) method. Design/methodology/approach The weighted numerical particles are adopted in a similar manner to the multi-Monte Carlo (MMC) method, with the addition of a new fraction function (alpha). Probabilistic removal is also introduced to maintain a constant number scheme. Findings Three typical cases with constant kernel, free-molecular coagulation kernel and different initial distributions for particle coagulation are simulated and validated. The results show an excellent agreement between the Monte Carlo (MC) method and the corresponding analytical solutions or sectional method results. Further numerical results show that the critical stochastic error in the newly proposed WFMC method is significantly reduced when compared with the traditional MMC method for higher-order moments with only a slight increase in computational cost. The particle size distribution is also found to extend for the larger size regime with the WFMC method, which is traditionally insufficient in the classical direct simulation MC and MMC methods. The effects of different fraction functions on the weight function are also investigated. Originality Value Stochastic error is inevitable in MC simulations of aerosol dynamics. To minimize this critical stochastic error, many algorithms, such as MMC method, have been proposed. However, the weight of the numerical particles is not adjustable. This newly developed algorithm with an adjustable weight of the numerical particles can provide improved stochastic error reduction.

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