Application of extended method of classes for solving population balance equations and optimization study for crystallization process involving dissolution phenomena
Crystallization is a well-established chemical process for producing high quality of crystals. Several phenomena such as nucleation, crystal growth and dissolution are involved in producing good crystal's quality. Thus modelling of crystallization process is essential for representing crystal q...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IOP Publishing Ltd
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/35841/ http://umpir.ump.edu.my/id/eprint/35841/1/Application%20of%20extended%20method%20of%20classes%20for%20solving%20population%20balance%20equations%20and%20optimization%20study%20for%20crystallization.pdf |
| Summary: | Crystallization is a well-established chemical process for producing high quality of crystals. Several phenomena such as nucleation, crystal growth and dissolution are involved in producing good crystal's quality. Thus modelling of crystallization process is essential for representing crystal quality as well as for process control and optimization purposes. One of the widely approach to represent crystal quality in terms of crystal size distribution (CSD) and to solve population balance equations (PBE) is by using method of classes (MOC). However, MOC is only applicable for the case of nucleation and crystal growth and thus needs to be extended for the case of dissolution. Therefore, the objective of this paper is to extend MOC for the case of dissolution and demonstrate crystallization process involving dissolution in order to achieve desired CSD with minimum fine crystals. The mathematical model of the process is developed and simulated in Matlab. The optimization algorithm is employed to generate set-point trajectory for Proportional-Integral (PI) controller in the case of with and without dissolution phenomena. Based on the simulations, the MOC have shown comparable results with published literature, which indicates MOC has been successfully extended to solve the PBE and representing CSD for size dependent growth rate system. |
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