(205a) Compartmental Modeling and Simulation Study of Wet Twin Screw Granulator

A twin-screw wet granulator (TSWG) is an emerging technology for continuous wet granulation that achieves desired level of mixing through a combination of appropriate screw configuration and a range of process settings (e.g. feed rate, screw speed, etc.). The wet granulation process in TSWG can be divided into several stages. A number of different mechanisms, including nucleation, growth, aggregation, and breakage, which ultimately determine the characteristics of the produced granules, typically drive the dynamics of wet granulation. In this study, a laboratory scale TSWG is used to granulate α-Lactose monohydrate as a function of the screw speed, powder throughput and liquid to solid (L/S) ratio. The experimental results are used to construct and validate a Population Balance Model (PBM) of the granulator using the concept of compartmental modeling. The system is divided into three compartments based on the dominating process occurring in the respective compartments, i.e., first, second and third compartment are dedicated to aggregation, aggregation with breakage and breakage respectively. A recently developed discretization ([1] and [2]) is adapted and implemented to solve this model whose idea is based on the conserving the important properties of the system. The proposed model is analyzed by varying the liquid to solid (L/S) ratio as well as the rate of mass exchange between the compartments to track the particle size distribution. We find that the proposed mathematical model is capable of tracking the particle size distribution accurately for various values of L/S ratio and discuss the effect of these parameters on the performance of the granulator.

Keywords: Population Balance Equation, Twin Screw Wet Granulator, Finite volume Scheme.

References:

[1] Kumar, J., Kaur, G. and Tsotsas, E. (2016) An accurate and efficient discrete formulation of aggregation population balance equation. Kinetic and Related Models 9(2), 373-391.

[2] Saha, J., Kumar, J., Buck, A. and Tsotsas, E. (2016) Finite volume approximations of breakage population balance equation. Chemical Engineering Research and Design 110, 114-122.