LAPSE:2021.0359
Published Article
LAPSE:2021.0359
Rapid Multi-Objective Optimization of Periodically Operated Processes Based on the Computer-Aided Nonlinear Frequency Response Method
Luka A. Živković, Viktor Milić, Tanja Vidaković-Koch, Menka Petkovska
May 17, 2021
The dynamic optimization of promising forced periodic processes has always been limited by time-consuming and expensive numerical calculations. The Nonlinear Frequency Response (NFR) method removes these limitations by providing excellent estimates of any process performance criteria of interest. Recently, the NFR method evolved to the computer-aided NFR method (cNFR) through a user-friendly software application for the automatic derivation of the functions necessary to estimate process improvement. By combining the cNFR method with standard multi-objective optimization (MOO) techniques, we developed a unique cNFR−MOO methodology for the optimization of periodic operations in the frequency domain. Since the objective functions are defined with entirely algebraic expressions, the dynamic optimization of forced periodic operations is extraordinarily fast. All optimization parameters, i.e., the steady-state point and the forcing parameters (frequency, amplitudes, and phase difference), are determined rapidly in one step. This gives the ability to find an optimal periodic operation around a sub-optimal steady-state point. The cNFR−MOO methodology was applied to two examples and is shown as an efficient and powerful tool for finding the best forced periodic operation. In both examples, the cNFR−MOO methodology gave conditions that could greatly enhance a process that is normally operated in a steady state.
Keywords
computer-aided nonlinear frequency response, cost–benefit indicator analysis, dynamic multi-objective optimization, forced periodic regime, Process Intensification
Suggested Citation
Živković LA, Milić V, Vidaković-Koch T, Petkovska M. Rapid Multi-Objective Optimization of Periodically Operated Processes Based on the Computer-Aided Nonlinear Frequency Response Method. (2021). LAPSE:2021.0359
Author Affiliations
Živković LA: Faculty of Technology and Metallurgy, University of Belgrade, 11060 Belgrade, Serbia; Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany
Milić V: Faculty of Technology and Metallurgy, University of Belgrade, 11060 Belgrade, Serbia
Vidaković-Koch T: Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany [ORCID]
Petkovska M: Faculty of Technology and Metallurgy, University of Belgrade, 11060 Belgrade, Serbia [ORCID]
Journal Name
Processes
Volume
8
Issue
11
Article Number
E1357
Year
2020
Publication Date
2020-10-27
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr8111357, Publication Type: Journal Article
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LAPSE:2021.0359
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doi:10.3390/pr8111357
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May 17, 2021
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May 17, 2021
 
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Calvin Tsay
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