Optimization of batch cooling crystallization systems considering crystal growth, nucleation and dissolution. Part I: Simulation--颗粒学报PARTICUOLOGY

Xu, Q., Lian, B., Long, Y., Shan, B., Wang, X., & Zhang, F. (2025). Optimization of batch cooling crystallization systems considering crystal growth, nucleation and dissolution. Part I: Simulation. Particuology, 96, 84-96. https://doi.org/10.1016/j.partic.2024.10.018

Optimization of batch cooling crystallization systems considering crystal growth, nucleation and dissolution. Part I: Simulation

Qilei Xu^a, Bin Lian^a, Yan Long^a, Baoming Shan^a, Xuezhong Wang^{b c}, Fangkun Zhang ^a *

a College of Automation and Electronic Engineering, Qingdao University of Science & Technology, Qingdao, 266061, China
b School of Chemical and Process Engineering, University of Leeds, Leeds, LS2 9JT, United Kingdom
c Centre for Pharmaceutical and Crystallization Process Systems Engineering, School of Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing, 102617, China

10.1016/j.partic.2024.10.018

Volume 96, Received 15 August 2024, Revised 11 October 2024, Accepted 27 October 2024, Available online 9 November 2024, Version of Record 21 November 2024., Pages 84-96

January 2025

E-mail: f.k.zhang@hotmail.com

Highlights

• A new method with new objective function and improved optimization algorithm was proposed for optimal control of CSD.

• Optimal control of CSD with suppressed numerical discrepancy was developed by combining seed recipe and temperature-swing.

• A newly constructed sinusoidal weight function was used to improve the particle swarm optimization algorithm.

• Two cases demonstrated fine crystal mass and number can be reduced by over 90% by the integrated optimization approach.

Abstract

Optimal control of batch crystallization systems is still a focus and hot topic in the field of industrial crystallization, which seriously affects the consistency of batch product quality. In this paper, a new method with a new objective function and improved optimization algorithm was proposed for optimization of crystal size distribution (CSD) in case of fine crystals occurrence. The new objective function was developed with better margin metric and weighting technique to minimize fine crystal mass, meanwhile, a newly constructed sinusoidal weight function was introduced to improve the particle swarm optimization (PSO) algorithm. A precise control of CSD with suppressed numerical discrepancy caused by fine crystals removal was developed by combining seed recipe and temperature-swing. In addition, the effects of temperature curve segments on CSD during process optimization were systematically investigated to achieve optimal results. Two typical batch cooling crystallization systems were used to verify the effectiveness of the proposed method in controlling product CSD while minimizing fine crystal mass. Results demonstrated that the desired product CSD can be achieved with minor errors while the fine crystals could be shrunk to be negligible, i.e., the fine crystal mass and number can be reduced by over 90%. This work has an important guiding significance for the removal of fine crystals in industrial crystallization processes, especially when only operational optimization rather than equipment updating is considered.

Graphical abstract

Keywords

Crystal size distribution; Optimization; Objective function; Fine crystals removal; Batch crystallization

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