求解考虑颗粒凝并的通用动力学方程的多重Monte Carlo算法

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

MonteCarlo(MC)方法被广泛用于通用动力学方程的求解,然而普通MC方法的计算代价较高而计算精度不稳定· 提出一种新的多重MonteCarlo(MMC)算法来求解GDE,该算法同时具有基于时间驱动MC方法、常数目法和常体积法的特点· 首先详细介绍了该算法,包括加权虚拟颗粒的引入,MMC算法的计算流程,时间步长的设置,颗粒是否发生凝并事件的判断,凝并伙伴的寻找,凝并事件的后果处理· 然后利用MMC算法对存在理论分析解的5种特殊工况进行数值求解,模拟结果与理论解符合很好,证明MMC算法具有良好的计算精度和较低的计算代价· 最后分析了不同类型的凝并核对于凝并过程的影响,常凝并核和连续区布朗凝并核对小颗粒影响大一些。

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.