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

Raquel Busqué (), Matias Bossio, Raimon Fabregat, Francesc Bonada, Héctor Maicas, Jordi Pijuan and Albert Brigido
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Raquel Busqué: Product Innovation & Multiphysics Simulation Unit, Eurecat, Centre Tecnològic de Catalunya, Av. Universitat Autònoma 23, 08290 Cerdanyola del Vallès, Spain
Matias Bossio: Product Innovation & Multiphysics Simulation Unit, Eurecat, Centre Tecnològic de Catalunya, Av. Universitat Autònoma 23, 08290 Cerdanyola del Vallès, Spain
Raimon Fabregat: Applied Artificial Intelligence Unit, Eurecat, Centre Tecnològic de Catalunya, Av. Universitat Autònoma 23, 08290 Cerdanyola del Vallès, Spain
Francesc Bonada: Applied Artificial Intelligence Unit, Eurecat, Centre Tecnològic de Catalunya, Av. Universitat Autònoma 23, 08290 Cerdanyola del Vallès, Spain
Héctor Maicas: Metallic and Ceramic Materials Unit, Eurecat, Centre Tecnològic de Catalunya, Plaça de la Ciència 2, 08243 Manresa, Spain
Jordi Pijuan: Departament d’Enginyeria Industrial i de l’Edificació, Universitat de Lleida, Jaume II 69, 25003 Lleida, Spain
Albert Brigido: Product Innovation & Multiphysics Simulation Unit, Eurecat, Centre Tecnològic de Catalunya, Av. Universitat Autònoma 23, 08290 Cerdanyola del Vallès, Spain

Energies, 2025, vol. 18, issue 11, 1-13

Abstract: 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.

Keywords: heat sink; topology optimization; data-driven optimization; computational fluid dynamics; experimental validation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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