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  4. Multi-objective optimization superimposed model-based process design of an enzymatic hydrolysis process
 
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Multi-objective optimization superimposed model-based process design of an enzymatic hydrolysis process

Publikationstyp
Journal Article
Date Issued
2017-01-05
Sprache
German
Author(s)
Zitzewitz, Philip  
Fieg, Georg  
Institut
Prozess- und Anlagentechnik V-4  
TORE-URI
http://hdl.handle.net/11420/3182
Journal
AIChE journal  
Volume
63
Issue
6
Start Page
1974
End Page
1988
Citation
AIChE Journal 6 (63): 1974-1988 (2017-06-01)
Publisher DOI
10.1002/aic.15609
Scopus ID
2-s2.0-85008144269
Publisher
American Institute of Chemical Engineers
The concepts of green process engineering and rigorous model-based approaches have proven to be highly beneficial in process engineering. Although a combination of these two principles thus appears extremely promising, it is not found very commonly in literature. The very high complexity resulting from this combination poses great challenges for the process design and design engineers. Therefore, this work presents an innovative methodology for the model-based process design with superimposed multi-objective optimization for an exemplary process. This process for the enzymatic hydrolysis of fatty acid methyl ester combines several aspects of green process engineering and represents an exemplary process with an enzymatic liquid-liquid-solid reaction system. The optimization results based on operating and investment costs reveal important insights on the exemplary process and highlight the great advantages of the developed methodology as a profound basis for academic and industrial process design purposes. © 2017 American Institute of Chemical Engineers AIChE J, 63: 1974–1988, 2017.
Subjects
enzymatic hydrolysis
mathematical modeling
process design
multi-objective optimization
DDC Class
540: Chemie
600: Technik
More Funding Information
The authors would like to thank the Federal Ministry for Economic Affairs and Energy (BMWi) represented by the “German Federation of Industrial Research Associations” (AiF) for funding the research project (IGF- Nr.17673 N).
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