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Metaheuristic Framework for Material Screening and Operating Optimization of Adsorption-Based Heat Pumps

Title
Metaheuristic Framework for Material Screening and Operating Optimization of Adsorption-Based Heat Pumps
Type
Article in International Scientific Journal
Year
2023
Authors
Silva, BC
(Author)
Other
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Rebello, CM
(Author)
Other
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Rodrigues, AE
(Author)
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Ana M. Ribeiro
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FEUP
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Alexandre Ferreira
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FEUP
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Nogueira, IBR
(Author)
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Journal
Title: ACS OmegaImported from Authenticus Search for Journal Publications
Vol. 8
Indexing
Other information
Authenticus ID: P-00Y-M6V
Abstract (EN): The current methods applied to material screening foradsorption-basedheat pumps are based on a fixed set of temperatures or their independentvariation, providing a limited, insufficient, and unpractical evaluationof different adsorbents. This work proposes a novel strategy for thesimultaneous optimization and material screening in the design ofadsorption heat pumps by implementing a meta-heuristic approach, particleswarm optimization (PSO). The proposed framework can effectively evaluatevariable and broad operation temperature intervals to search for viablezones of operation for multiple adsorbents at once. The criteria forselecting the adequate material were the maximum performance and theminimum heat supply cost, which were considered the objective functionsof the PSO algorithm. First, the performance was assessed individually,followed by a single-objective approximation of the multi-objectiveproblem. Next, a multi-objective approach was also adopted. With theresults generated during the optimization, it was possible to findwhich adsorbents and temperature sets were the most suitable accordingto the main objective of the operation. The Fisher-Snedecortest was applied to expand the results obtained during PSO applicationand a feasible operating region built around the optima, enablingthe arrangement of close-to-optima data into practical design andcontrol tools. This approach allowed for a fast and intuitive evaluationof multiple design and operation variables.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 18
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