A bimodal moment method model for submicron fractal-like agglomerates undergoing Brownian coagulation

Abstract

A new bimodal moment method for submicron fractal-like agglomerates undergoing Brownian coagulation is developed. The entire bimodal agglomerate size distribution is firstly separated into two separated distributions, where each distribution is represented by a population balance equation. The two joint population balance equations are then resolved by introducing the Taylor expansion method of moments (TEMOM). This newly developed bimodal model (B-TEMOM) is compared with the commonly used bimodal log-normal method of moments (B-log MM), and bimodal quadrature method of moments (B-QMOM) for the first three moments as well as geometric standard deviation of number distribution. Compared to the B-QMOM, the solution suggests that the B-TEMOM and the B-log MM produce much closer results. With the increase in the difference of the total particle number concentration, the geometric standard deviation, and the geometric mean volume of two modes, the difference among the investigated bimodal models is also slightly increased. The difference between B-log MM and B-TEMOM is found to increase with a decrease in mass fractal dimension, especially at a later stage in the evolution. The solution fully verifies that this newly developed B-TEMOM is reliable for predicting agglomerate dynamics undergoing Brownian coagulation in the continuum-slip regime.