模拟颗粒凝并过程的快速Monte Carlo方法

对常规异权值Monte Carlo(MC)方法进行改进,基于强核函数思想,通过颗粒群单重遍历即可求得强核函数最大值,采用接受-拒绝法随机搜寻凝并对,并利用搜寻过程中拒绝和接受的所有凝并对的信息来估计凝并事件的等待时间(时间步长),从而避免颗粒群的双重遍历,以提高MC的效率.对典型工况的模拟结果显示该快速方法计算代价仅为O(N_s),能够显著提高计算效率,同时保持足够的计算精度,较好地协调计算代价与计算精度之间的矛盾.

Fast Monte Carlo Method for Particle Coagulation Dynamics

We propose a fast random simulation strategy based on differentially weighted MC. The strategy improves computation efficiency significantly, and guarantees enough calculation accuracy, thus coordinates contradiction between computation cost and computation accuracy. The main idea is based on majorant kernel. It is possible to transfer a traditional coagulation kernel to a majorant kernel through splitting and amplifying slightly. The maximum of majornant kernel is obtained by single looping over all simulation particles. The maximum majornant kernel is used to approximate the maximum coagulation kernel in particle population, and is further used to search coagulation particle pairs randomly with acceptance-rejection method. The waiting time (time-step) for a coagulation event is calculated by summing coagulation kerenls of particle pairs involved in acceptance/rejection processes.. Double looping in normal Monte Carlo simulation is avoided and computation efficiency is improved greatly.