Analysis of mesoscale effects in high-shear granulation through a computational fluid dynamics–population balance coupled compartment model

Abstract

In high shear granulation it has been pointed out that there is a need for meso-scale resolution and coupling between flow field information and the evolution of particle properties. In this article we develop a modelling framework that compartmentalizes the high shear granulation process based on process relevant parameters both in time and space. It is built up by a coupled flow field and population balance solver and is used to resolve and analyze the effects of meso-scales on the evolution of particle properties. A Diosna high shear mixer is modelled with micro crystalline cellulose powder as the granulation material. The analysis of the flow field solution and compartmentalization allows for a resolution of the stress and collision peak at the impeller blades. Different compartmentalizations were done showing the importance of resolving the impeller region, both for only aggregating systems and systems with breakage. An investigation on the time evolution of the flow field depending on the changing particle properties was also done, indicating the importance of resolving meso scale phenomena in time as well as space.

A predictive PBM-DEAM model for lignocellulosic biomass pyrolysis

“…The population balance equations were firstly presented by Hulburt and Katz [16] in 1964, calculating the particle size distribution of the dispersed phase. Since then, the Population Balance Model (PBM) has been popularly introduced to particles in process modelling (e.g., the granulation [17][18][19] and crystallization [20] processes), to investigate the way of change in biomass particle size distribution. Basic mechanisms of the PBM for evolution of the particle size distribution are: nucleation, growth, aggregation and breakage [21].…”

Coupled Population Balance and Species Balance Models of Crystallization: Analytic Solutions and Data Fits

“…Later work by Randolph and Larson , and Timm numerically solved PBEs with more advanced nucleation models, , accounting for variations in both supersaturation and magma density. Their analysis found that numerical solutions became difficult as the order of exponent on supersaturation with the nucleation model increases. ,,, In subsequent years, numerical solution techniques have become far more robust and sophisticated. − Nevertheless, there are practical advantages to analytic PBE solutions, where they can be obtained.…”