A Fast Monte Carlo Method Based on an Acceptance-Rejection Scheme for Particle Coagulation

Wei, Jianming

doi:10.4209/aaqr.2012.12.0369

Cited by 10 publications

(7 citation statements)

References 26 publications

(31 reference statements)

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“…Coagulation particle pairs can be randomly selected by the cumulative probability method (Liffman, 1992) or the acceptance-rejection method (Lin et al , 2002). However, the acceptance-rejection method adopts a simpler and more straightforward criterion for selecting the particle pairs compared with the cumulative probability method (Wei, 2013). Hence, the acceptance-rejection method is used in the present study.…”

Section: Description Of the Weighted Fraction Monte Carlo Methodsmentioning

confidence: 99%

A new weighted fraction Monte Carlo method for particle coagulation

Jiang

Chan

2021

HFF

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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 (α). 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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Section: Description Of the Weighted Fraction Monte Carlo Methodsmentioning

confidence: 99%

A new weighted fraction Monte Carlo method for particle coagulation

Jiang

Chan

2021

HFF

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“…The GPU has off-chip global memory and on-chip shared memory [26,27]. This enables the programmer to select the type of memory used according to the requirement of the kernel [28].…”

Section: )mentioning

confidence: 99%

The Computational Efficiency of Monte Carlo Breakage of Articles using Serial and Parallel Processing: A Comparison

Devi¹,

Kumar²

2019

IJACSA

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This paper presents a GPU-based parallelized and a CPU-based serial Monte-Carlo method for breakage of a particle. We compare the efficiency of the graphic card's graphics processing unit (GPU) and the general-purpose central processing unit (CPU), in a simulation using Monte Carlo (MC) methods for processing the particle breakage. Three applications are used to compare the computational performance times, clock cycles and speedup factors, to find which platform is faster under which conditions. The architecture of the GPU is becoming increasingly programmable; it represents a potential speedup for many applications compared to the modern CPU. The objective of the paper is to compare the performance of the GPU and Intel Core i7-4790 multicore CPU. The implementation for the CPU was written in the C programming language, and the GPU implemented the kernel using Nvidia's CUDA (Compute Unified Device Architecture). This paper compares the computational times, clock cycles and the speedup factor for a GPU and a CPU, with various simulation settings such as the number of simulation entries (SEs), for a better understanding of the GPU and CPU computational efficiency. It has been found that the number of SEs directly affects the speedup factor.

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“…Nevertheless, the initial form of the particle size distribution should be assumed to obtain the closure of the moment equations, and it is difficult to give particle size distributions. Moreover, it becomes complicated and difficult when solving multi-component particle systems using the MOM and SM [20][21][22]. While the MC method is relatively straightforward for solving the complex multidimensional and multicomponent particle systems, it is also easy to find the internal information and the historical trajectory of the aerosols [23,24].…”

Section: Introductionmentioning

confidence: 99%

Numerical Modeling of Droplet Aerosol Coagulation, Condensation/Evaporation and Deposition Processes

et al. 2022

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The differentially weighted operator-splitting Monte Carlo (DWOSMC) method is further developed to describe the droplet aerosol dynamic behaviors, including coagulation, deposition, condensation, and evaporation processes. It is first proposed that the droplet aerosols will experience firstly condensation and then evaporation, and this phenomenon is first implemented into the Monte Carlo method and sectional method with considering coagulation, deposition, and condensation/evaporation processes in both single-component and two-component aerosol particle systems. It is found that the calculated results of the DWOSMC method agree well with both the analytical solutions and the sectional method. The further developed DWOSMC method can predict the variation of particle number density, total particle volume, mean particle diameter, particle size distributions, and the component-related particle volume densities in both single component and two-component droplet aerosol systems considering coagulation, deposition, and condensation/evaporation processes.

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A Fast Monte Carlo Method Based on an Acceptance-Rejection Scheme for Particle Coagulation

Cited by 10 publications

References 26 publications

A new weighted fraction Monte Carlo method for particle coagulation

A new weighted fraction Monte Carlo method for particle coagulation

The Computational Efficiency of Monte Carlo Breakage of Articles using Serial and Parallel Processing: A Comparison

Numerical Modeling of Droplet Aerosol Coagulation, Condensation/Evaporation and Deposition Processes

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