Population balance modelling of fluidized bed melt granulation : An overview

• Published in: Chemical engineering research & design 2005-07, Vol.83 (7), p.871-880
• Main Authors: TAN, H. S, GOLDSCHMIDT, M. J. V, BOEREFIJN, R, HOUNSLOW, M. J, SALMAN, A. D, KUIPERS, J. A. M
• Format: Article
• Language: English
• Subjects: Applied sciences; Chemical engineering; Exact sciences and technology; Fluidization; Miscellaneous; Sintering, pelletization, granulation; Solid-solid systems
• ISSN: 0263-8762
• DOI: 10.1205/cherd.04347

This paper presents an overview of the work undertaken by our group to identify and quantify the rates processes active in fluidized bed melt granulation (FBMG). The process involves the identification and development of physically representative models to mechanistically describe FBMG using both theoretical and experimental means. The development of an aggregation model involves the use of the kinetic theory of granular flow to identify an aggregation model based on the description of the particle collision rate for multi-components mixture in fluidized bed. This model is analogous to the equipartition of the kinetic energy (EKE) model and thus serves as its theoretical basis. The process of selecting a breakage model involves the coupling of tracer experiments with two dimensional (2-D) population balance modelling to identify and validate the breakage model. The breakage function describes the breaking of granule into two larger fragments and some smaller fragments (i.e., primaries) while the selection rate function is taken to be size and time independent. Two different approaches have been taken to model a range of experimental data obtained at various operating conditions using a discretized population balance model: (1) modelling the net rate of granule growth; and (2) simultaneous modelling of the aggregation and breakage process. Both techniques describes the experimental granule size distributions well, thereby allowing us to relate the extracted rate constants to process conditions and interpret their influence on granulation kinetics.