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Modelling of crystallization process and optimization of the cooling strategy

Authors
Kim, Do YeonPaul, MichaellaRapke, Jens-UweWozny, GuenterYang, Dae Ryook
Issue Date
9월-2009
Publisher
SPRINGER
Keywords
Optimal Cooling; Batch Crystallization; Meta-stable Zone; Genetic Algorithm
Citation
KOREAN JOURNAL OF CHEMICAL ENGINEERING, v.26, no.5, pp.1220 - 1225
Indexed
SCIE
SCOPUS
KCI
Journal Title
KOREAN JOURNAL OF CHEMICAL ENGINEERING
Volume
26
Number
5
Start Page
1220
End Page
1225
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/119460
DOI
10.1007/s11814-009-0207-6
ISSN
0256-1115
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 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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