Modelling of crystallization process and optimization of the cooling strategy

Do Yeon Kim, Michaella Paul, Jens Uwe Rapke, Günter Wozny, Dae Ryook Yang

    Research output: Contribution to journalArticlepeer-review

    12 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)1220-1225
    Number of pages6
    JournalKorean Journal of Chemical Engineering
    Volume26
    Issue number5
    DOIs
    Publication statusPublished - 2009 Sept

    Keywords

    • Batch Crystallization
    • Genetic Algorithm
    • Meta-stable Zone
    • Optimal Cooling

    ASJC Scopus subject areas

    • General Chemistry
    • General Chemical Engineering

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