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Model‐Based Optimization of Ripening Processes with Feedback Modules
Author(s) -
Spinola Michele,
Keimer Alexander,
Segets Doris,
Leugering Günter,
Pflug Lukas
Publication year - 2020
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.201900515
Subject(s) - process engineering , process (computing) , product (mathematics) , variable (mathematics) , computer science , population , flow (mathematics) , quality (philosophy) , mathematical optimization , control theory (sociology) , engineering , mathematics , mechanics , physics , control (management) , mathematical analysis , geometry , demography , quantum mechanics , artificial intelligence , sociology , operating system
In order to obtain high‐quality particulate products with tailored properties, process conditions and their evolution in time must be chosen appropriately. Although the efficiency of these products depends on their dispersity in several dimensions, in established processes the particle size is usually the decisive variable to adjust. As part of the synthesis of these products, feedback modules are often incorporated so that a time‐dependent ratio of the obtained product can flow back into the system. Moreover, the synthesis should be an energy‐ and resource‐efficient process. To provide a means of ensuring this requirement, a model‐ and gradient‐based, numerically efficient optimization tool for particle synthesis is presented which was developed to describe population balance equations incorporating feedback terms.