Multi-Monte Carlo Method for General Dynamic Equation Considering Particle Coagulation

ZHAO Hai-bo; ZHENG Chu-guang; XU Ming-hou

Article Contents

Article Navigation > Applied Mathematics and Mechanics > 2005 > 26(7): 875-882

ZHAO Hai-bo, ZHENG Chu-guang, XU Ming-hou. Multi-Monte Carlo Method for General Dynamic Equation Considering Particle Coagulation[J]. Applied Mathematics and Mechanics, 2005, 26(7): 875-882.

Citation:

ZHAO Hai-bo, ZHENG Chu-guang, XU Ming-hou. Multi-Monte Carlo Method for General Dynamic Equation Considering Particle Coagulation[J]. Applied Mathematics and Mechanics, 2005, 26(7): 875-882.

Citation:

ZHAO Hai-bo, ZHENG Chu-guang, XU Ming-hou. Multi-Monte Carlo Method for General Dynamic Equation Considering Particle Coagulation[J]. Applied Mathematics and Mechanics, 2005, 26(7): 875-882.

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Multi-Monte Carlo Method for General Dynamic Equation Considering Particle Coagulation

State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, Wuhan 430074, P. R. China

Received Date: 2004-08-12
Rev Recd Date: 2005-03-08
Publish Date: 2005-07-15

Abstract

Abstract

Monte Carlo (MC) method is widely adopted to take into account general dynamic equation (GDE) for particle coagulation, however popular MC method has high computation cost and statistical fatigue. A new Multi-Monte Carlo (MMC) method, which has characteristics of time-driven MC method, constant number method and constant volume method, was promoted to solve GDE for coagulation. Firstly MMC method was described in details, including the introduction of weighted fictitious particle, the scheme of MMC method, the setting of time step, the judgment of the occurrence of coagulation event, the choice of coagulation partner and the consequential treatment of coagulation event. Secondly MMC method was validated by five special coagulation cases in which analytical solutions exist. The good agreement between the simulation results of MMC method and analytical solutions shows MMC method conserves high computation precision and has low computation cost. Lastly the different influence of different kinds of coagulation kernel on the process of coagulation was analyzed: constant coagulation kernel and Brownian coagulation kernel in continuum regime affect small particles much more than linear and quadratic coagulation kernel, whereas affect big particles much less than linear and quadratic coagulation kernel.
- numerical solution,
- population balance equation,
- fictitious particle,
- particle size distribution,
- constant kernel,
- computation cost,
- computation precision

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References(13)

References

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