A bimodal moment model for the simulation of particle growth

Abstract

A computationally efficient bimodal moment model was proposed to describe simultaneous particle formation, coagulation, and surface growth. In the model framework, two discrete modes are introduced to represent a bimodal size distribution: one monodisperse mode accounting for the formation of new particles in the nucleation mode and the other accumulation mode for the growth of the larger particles. The size distribution of the accumulation mode could be approximated by a proper mathematical function. General formulation of the bimodal moment model is first presented, and a bimodal log-normal model (bi-LN model) is described by adopting a log-normal function for the accumulation mode. The prediction results of the proposed bimodal moment model were compared with those of a previous bimodal model and an accurate sectional model. It was demonstrated that the bi-LN model agreed well with the sectional model and correctly described the evolution of bimodal size distribution resulting from the coexistence of particle formation and coagulation. The bi-LN model was also shown to be capable of predicting the growth of particles involving simultaneous particle formation, coagulation and surface growth, which was validated by comparing with the simulation results by the moving sectional model.