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Monte Carlo simulation for the solution of the bi-variate dynamic population balance equation in batch particulate systems

机译:批粒系统中二元动态总体平衡方程求解的蒙特卡罗模拟

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摘要

This paper presents a study on the solution of the bi-variate population balance equation (PBE) in batch particulate processes using stochastic Monte Carlo (MC) simulations. Numerical simulations were carried out over a wide range of variation of particle aggregation and growth rate models. The PBE was numerically solved in terms of the number density function, n(V, x, t), for the prediction of the dynamic evolution of the two-dimensional (with respect to particle volume, V, and a second internal property, x) particle size distribution (PSD), as well as for the calculation of the leading moments of the distribution. The performance of the method was assessed in terms of accuracy via a direct comparison of the calculated PSDs and the respective leading moments to available analytical solutions. The comparisons showed that the MC algorithm was capable of predicting the dynamic evolution of the bi-variate distribution with high accuracy, while its computational requirements were relatively low. (c) 2006 Elsevier Ltd. All rights reserved.
机译:本文介绍了使用随机蒙特卡洛(MC)模拟对批次粒子过程中的双变量总体平衡方程(PBE)进行求解的研究。在粒子聚集和生长速率模型的广泛变化范围内进行了数值模拟。用数字密度函数n(V,x,t)对PBE进行数值求解,以预测二维(相对于粒子体积V和第二内部性质x)的动态演化)粒径分布(PSD),以及用于计算分布的前导矩。通过将计算出的PSD和相应的领先时刻与可用的分析解决方案进行直接比较,以准确性评估了该方法的性能。比较表明,MC算法能够以较高的精度预测双变量分布的动态演变,而其计算需求却相对较低。 (c)2006 Elsevier Ltd.保留所有权利。

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