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Received January 6, 2009
Accepted February 12, 2009
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
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Modelling of crystallization process and optimization of the cooling strategy
Department of Chemical and Biological Engineering, Korea University, 1AnamDong 5Ga, SeongbukGu, Seoul, Korea 1Department of Process Dynamics and Operation, Technical University Berlin, Sekr. KWT 9,Str. 17. Juni 135, Berlin, 10623, Germany
Korean Journal of Chemical Engineering, September 2009, 26(5), 1220-1225(6), 10.1007/s11814-009-0207-6
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Abstract
To obtain a uniform and large crystal in seeded batch cooling crystallization, the cooling strategy is very important. In this study, an optimal cooling strategy is obtained through simulation and compared to linear and natural cooling strategies. A model for a crystallization process in a batch reactor is constructed by using population balance equation and material balance for solution concentration, and a prediction model for meta-stable limit is formulated by the dynamic meta-stable limit approach. Based on this model, an optimal cooling strategy is obtained using genetic_x000D_
algorithm with the objective function of minimizing the unwanted nucleation and maximizing the crystal growth rate. From the simulation results, the product from the optimal cooling strategy showed uniform and large crystal size distribution while products from the other two strategies contained significant amount of fine particles.
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Choong KL, Smith R, Chem. Eng. Sci., 59(2), 313 (2004)
Chang W, Exp. Sys. Appl., 33, 620 (2007)
