Model-based optimization for operational policies in seeded cooling crystallization
Document Type
Article
Publication Date
12-1-2006
Abstract
In this solution crystallization study, a population balance model that predicts the crystal size distribution (CSD) is used for targeting, by optimization, the product mean size and the coefficient of variation of the final CSD. The model is robust over a wide range of conditions and predicts the effects of heating during a batch since the kinetics of dissolution have been identified and incorporated into the model. The dynamic temperature profile and the initial seed size distribution are optimized while the initial seed induction time is conferred through knowledge of saturation conditions. This is quite a highly developed approach in contrast to existing anecdotal and/or rule-of-thumb experience currently dictating industrial operational methods. Results from optimizations under different objective functions are presented and validated experimentally. © 2006 Elsevier B.V. All rights reserved.
Publication Source (Journal or Book title)
Computer Aided Chemical Engineering
First Page
1347
Last Page
1352
Recommended Citation
Abbas, A., Mostafa Nowee, S., & Romagnoli, J. (2006). Model-based optimization for operational policies in seeded cooling crystallization. Computer Aided Chemical Engineering, 21 (C), 1347-1352. https://doi.org/10.1016/S1570-7946(06)80234-8