(226e) Two-Compartmental Population Balance Modeling of a Pulsed Spray Fluidized Bed Granulation Based on Computational Fluid Dynamics (CFD) Analysis

Process models based on the one-dimensional discretized population balance model (PBM) are frequently adopted to describe a fluidized bed granulation process in which it is assumed that the fluidized bed is a well-mixed system and the mechanisms of the aggregation and breakage are spatially homogeneous for evolution of granule growth. However, it is well known that particles in a fluidized bed are not homogeneously distributed and their hydrodynamics and kinetic parameters concerning the size enlargement process change with the time and position in the bed. Therefore, the PBM based on homogeneity cannot be applied across the entire fluidized bed granulation process. It is essential to consider different granulation mechanisms according to different zones in a granulation process model to accurately predict the evolution of granule growth during granulation, which provides the potential for multi-compartmental modeling. In literature, very little research has been carried out investigating a multi-compartmental model for a spray fluidized bed granulation process.

In this work, a two-compartmental population balance model (TCPBM) was proposed to model a pulsed top-spray fluidized bed granulation. The proposed TCPBM considered the spatially heterogeneous granulation mechanisms of the granule growth by dividing the granulator into two perfectly mixed zones of the wetting compartment and drying compartment, in which the aggregation mechanism was assumed in the wetting compartment and the breakage mechanism was considered in the drying compartment. The sizes of the wetting and drying compartments were constant in the TCPBM, in which 30% of the bed was the wetting compartment and 70% of the bed was the drying compartment. The exchange rate of particles between the wetting and drying compartments was determined by the details of the flow properties and distribution of particles predicted by the computational fluid dynamics (CFD) simulation. The experimental validation has shown that the proposed TCPBM can predict evolution of the granule size and distribution within the granulator under different binder spray operating conditions accurately.