Predictions of compositional mixing degree in two-component aggregation

doi:10.7523/j.issn.2095-6134.2017.02.013

Abstract

Abstract: Multi-component particle aggregation is one of the main physical mechanisms in the process of particle growth. For two-component aggregation, the compositional mixing degree χ is an important criterion and the key to determination of compositional distribution. Now the dynamic evolution of χ before the attainment of a steady-state value is beyond numerical modeling and theoretical research. In this work, the fast differentially-weighted Monte Carlo method for population balance modeling was used to predict the dependence of time-varied χ on initial feeding conditions through hundreds of systematically varied simulations. It is found that χ is subject to exponential decay in the free molecular regime and the continuum regime. By using the explored exponential formulas for the dynamic mixing degree, it is possible to achieve an optimum control over the compositional distributions during two-component aggregation processes through selecting the initial feeding parameters.

Key words: population balance modeling, two-component aggregation, Monte Carlo method, compositional mixing degree

CLC Number:

O359

ZHAO Hanqing, XU Zuwei, ZHAO Haibo. Predictions of compositional mixing degree in two-component aggregation[J]. , 2017, 34(2): 204-209.

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