A direct simulation Monte-Carlo method for cluster coagulation
Journal of Computational Physics
A stochastic weighted particle method for the Boltzmann equation
Journal of Computational Physics
Journal of Computational Physics
An Efficient Stochastic Algorithm for Studying Coagulation Dynamics and Gelation Phenomena
SIAM Journal on Scientific Computing
An efficient stochastic algorithm for simulating Nano-particle dynamics
Journal of Computational Physics
A stochastic approach for the numerical simulation of the general dynamics equation for aerosols
Journal of Computational Physics
A new numerical approach for the simulation of the growth of inorganic nanoparticles
Journal of Computational Physics
Journal of Computational Physics
A differentially weighted Monte Carlo method for two-component coagulation
Journal of Computational Physics
Coupling Algorithms for Calculating Sensitivities of Smoluchowski's Coagulation Equation
SIAM Journal on Scientific Computing
Weighted Flow Algorithms (WFA) for stochastic particle coagulation
Journal of Computational Physics
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Direct simulation Monte Carlo (DSMC) method is an important approach for numerical solution of the population balance equation, which characterizes the dynamic evolution of particle size distribution in dispersed systems. One sample of the whole system (i.e., subsystem) is taken into account in most DSMC methods. It means that a spatially-isotropic whole system is considered, and simulation particles having same number weight are tracked. A new event-driven constant-volume (EDCV) method for population balance modeling is proposed to describe the dynamic evolution in dispersed systems under influence of coagulation, breakage, nucleation, surface growth/dissolution (condensation/evaporation) and deposition (settling). The method adopts the concept of differentially weighting simulation particles, and several schemes of sample restoration are developed to maintain simulation particle number within prescribed bounds, at the same time the constant-volume computational domain is tracked. By comparing of several popular Monte Carlo methods, it is concluded that the proposed EDCV method exhibits comparatively high precision and efficiency.