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Journal of Shanghai University >

2020 , Vol. 26 >Issue 4: 617 - 627

DOI: https://doi.org/10.12066/j.issn.1007-2861.2055

Multi-Monte Carlo simulation for bicomponent coalescence in finite system

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  • Shanghai Institute of Applied Mathematics & Mechanics, Shanghai University, Shanghai 200072, China

Received date: 2017-04-11

  Online published: 2018-12-21

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Abstract

The mixing state of a bicomponent population of granules is characterized by the total variance of component A, which measures the deviation of the composition of each granule from the overall mean. By means of the multi-weighted Monte Carlo method, first the fundamental influence of the homogeneity index lambda of the kernel is verified, and the scaling rate of segregation index, which is a function of homogeneity index lambda, is obtained. Second, two stages in the evolution of mixing are identified. Before the critical time, both interaction between components and the kernel take important effects on the coalescence. And the repulsive interaction is much stronger than the attractive interaction. After the critical time, only the kernel itself affects the coalescence and the effects of interaction between components are ignored. Finally, a power-law function between the critical time and alpha is obtained, whereas an exponential function relationship between the critical time and $\lambda$ is identified by a curve fitting technique. The results are of great importance in the pharmaceutical engineering.

Key words： bi-component granules; finite system; composition-dependent kernel; segregation index; homogeneity index

Cite this article

ZUO Hao, SHEN Jie, LU Zhiming . Multi-Monte Carlo simulation for bicomponent coalescence in finite system[J]. Journal of Shanghai University, 2020 , 26(4) : 617 -627 . DOI: 10.12066/j.issn.1007-2861.2055

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