Population balance model versus lumped model for emulsion polymerisation: Semi-batch and continuous operation

In this article, a systematic comparison is made of a detailed population balance model of the emulsion polymerisation process that accounts for the dynamic evolution of the entire particle size distribution with a simple model of the process that accounts only for the dynamic evolution of the avera...

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Bibliographic Details
Published in:Chemical engineering research & design 2008-07, Vol.86 (7), p.692-702
Main Authors: Immanuel, Charles D., Pinto, Mark A., Richards, John R., Congalidis, John P.
Format: Article
Language:English
Subjects:
Applied sciences
Chemical engineering
Dynamic modeling
Emulsion polymerisation
Exact sciences and technology
Organic polymers
Particle nucleation
Particle size distribution
Physicochemistry of polymers
Polymerization
Population balances
Preparation, kinetics, thermodynamics, mechanism and catalysts
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Summary:In this article, a systematic comparison is made of a detailed population balance model of the emulsion polymerisation process that accounts for the dynamic evolution of the entire particle size distribution with a simple model of the process that accounts only for the dynamic evolution of the average particle size and the total particles. Both models account for the underlying mechanisms of the process to the level admissible within their respective frameworks. The predictions of the two models are compared under both batch and continuous operation. The aim is to elucidate the degree of disparity of model predictions for batch operation, and to elucidate the ability of the simple lumped models to predict oscillatory dynamics for continuous operation. The focus is on the comparison of the predictions of important control variables such as solids content (conversion), total particles and average particle size, but also those of important particle phenomena of nucleation, growth and coagulation. It is found that with respect to these lumped control variables, the simple model performs well in matching the detailed model, and hence will be a very valuable tool for the purpose of on-line feedback control. However, the detailed models will be important for distributed control variables such as the entire particle size distribution.
ISSN:0263-8762
1744-3563
DOI:10.1016/j.cherd.2008.01.011