Efficient Monte Carlo simulations of coagulation based on weighted particle strategies

In this paper, a class of efficient Monte Carlo methods based on weighted particle strategies for solving the coagulation population balance equation is presented. The adjustable coagulation resolution strategy is developed from probabilistic coagulation theories for general conditions. The particle reconstruction scheme accelerates simulations and reduces errors. Three components of the methods have been verified and validated against several benchmark coagulation scenarios with analytical solutions and a conventional constant-number method. The two methods, using stepwise-constant and size-dependent coagulation resolution, offer superior performance to the constant-number method in resolving regions with large and rare particles and higher-order moments without sacrificing computational efficiency. Moreover, the computation precision of both methods is significantly higher than the conventional methods, as the proposed method's precision is proportional to the square root of the total number of coagulation events rather than being dependent on the computational particle number used by conventional methods.