Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design

This study introduces a hybrid topology optimization methodology aimed at improving heat sink efficiency through a data-driven approach. The method integrates CFD simulations in Ansys Fluent with a Monte Carlo-driven optimization algorithm, modeling the design of a heat sink domain as a porous mediu...

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Detalles Bibliográficos
Autores: Busqué, Raquel, Bossio, Matias, Fabregat, Raimon, Bonada, Francesc, Maicas, Héctor, Pijuan, Jordi, Brigido, Albert
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/468309
Acceso en línea:https://doi.org/10.3390/en18112801
https://hdl.handle.net/10459.1/468309
Access Level:acceso abierto
Palabra clave:Heat sink
Topology optimization
Data-driven optimization
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spelling Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink DesignBusqué, RaquelBossio, MatiasFabregat, RaimonBonada, FrancescMaicas, HéctorPijuan, JordiBrigido, AlbertHeat sinkTopology optimizationData-driven optimizationThis study introduces a hybrid topology optimization methodology aimed at improving heat sink efficiency through a data-driven approach. The method integrates CFD simulations in Ansys Fluent with a Monte Carlo-driven optimization algorithm, modeling the design of a heat sink domain as a porous medium. Porosity is used as a design variable, iteratively adjusted in a binary manner to optimize fluid-solid distribution. Three design variants were evaluated, with the selected optimized configuration reaching a maximum temperature of 57.11 °C, compared to 46.15 °C for a baseline serpentine channel. Despite slightly higher peak temperature, the optimized design achieved a substantial reduction in pressure drop, up to 91.57%, translating into significantly lower pumping power requirements and thus lower energy consumption. Experimental validation, using physical prototypes of both the reference and optimized channels, confirmed strong agreement with simulation results, with average surface temperatures of 29.27 °C and 30.03 °C, respectively. These findings validate the accuracy of the simulation-based approach and highlight the potential of data-driven optimization in thermal management system designs.This work was financially supported by the Catalan Government through the funding grant ACCIÓ-Eurecat (Project TRAÇA M3DTALL).MDPI2025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.3390/en18112801https://hdl.handle.net/10459.1/468309reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a https://doi.org/10.3390/en18112801Energies, 2025, vol. 18, núm. 11, p. 2801cc-by (c) Busqué, Raquel et al., 2025info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/oai:recercat.cat:10459.1/4683092026-05-29T05:05:01Z
dc.title.none.fl_str_mv Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design
title Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design
spellingShingle Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design
Busqué, Raquel
Heat sink
Topology optimization
Data-driven optimization
title_short Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design
title_full Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design
title_fullStr Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design
title_full_unstemmed Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design
title_sort Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design
dc.creator.none.fl_str_mv Busqué, Raquel
Bossio, Matias
Fabregat, Raimon
Bonada, Francesc
Maicas, Héctor
Pijuan, Jordi
Brigido, Albert
author Busqué, Raquel
author_facet Busqué, Raquel
Bossio, Matias
Fabregat, Raimon
Bonada, Francesc
Maicas, Héctor
Pijuan, Jordi
Brigido, Albert
author_role author
author2 Bossio, Matias
Fabregat, Raimon
Bonada, Francesc
Maicas, Héctor
Pijuan, Jordi
Brigido, Albert
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Heat sink
Topology optimization
Data-driven optimization
topic Heat sink
Topology optimization
Data-driven optimization
description This study introduces a hybrid topology optimization methodology aimed at improving heat sink efficiency through a data-driven approach. The method integrates CFD simulations in Ansys Fluent with a Monte Carlo-driven optimization algorithm, modeling the design of a heat sink domain as a porous medium. Porosity is used as a design variable, iteratively adjusted in a binary manner to optimize fluid-solid distribution. Three design variants were evaluated, with the selected optimized configuration reaching a maximum temperature of 57.11 °C, compared to 46.15 °C for a baseline serpentine channel. Despite slightly higher peak temperature, the optimized design achieved a substantial reduction in pressure drop, up to 91.57%, translating into significantly lower pumping power requirements and thus lower energy consumption. Experimental validation, using physical prototypes of both the reference and optimized channels, confirmed strong agreement with simulation results, with average surface temperatures of 29.27 °C and 30.03 °C, respectively. These findings validate the accuracy of the simulation-based approach and highlight the potential of data-driven optimization in thermal management system designs.
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/en18112801
https://hdl.handle.net/10459.1/468309
url https://doi.org/10.3390/en18112801
https://hdl.handle.net/10459.1/468309
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a https://doi.org/10.3390/en18112801
Energies, 2025, vol. 18, núm. 11, p. 2801
dc.rights.none.fl_str_mv cc-by (c) Busqué, Raquel et al., 2025
info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv cc-by (c) Busqué, Raquel et al., 2025
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
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