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Energies
Volume 18
Issue 11
10.3390/en18112801
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

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

by
Raquel Busqué
1,*,
Matias Bossio
1,
Raimon Fabregat
2,
Francesc Bonada
2,
Héctor Maicas
3,
Jordi Pijuan
4 and
Albert Brigido
1
1
Product Innovation & Multiphysics Simulation Unit, Eurecat, Centre Tecnològic de Catalunya, Av. Universitat Autònoma 23, 08290 Cerdanyola del Vallès, Spain
2
Applied Artificial Intelligence Unit, Eurecat, Centre Tecnològic de Catalunya, Av. Universitat Autònoma 23, 08290 Cerdanyola del Vallès, Spain
3
Metallic and Ceramic Materials Unit, Eurecat, Centre Tecnològic de Catalunya, Plaça de la Ciència 2, 08243 Manresa, Spain
4
Departament d’Enginyeria Industrial i de l’Edificació, Universitat de Lleida, Jaume II 69, 25003 Lleida, Spain
*
Author to whom correspondence should be addressed.
Energies 2025, 18(11), 2801; https://doi.org/10.3390/en18112801
Submission received: 29 April 2025 / Revised: 20 May 2025 / Accepted: 26 May 2025 / Published: 27 May 2025
(This article belongs to the Special Issue Numerical Simulation Techniques for Fluid Flows and Heat Transfer)
Versions Notes

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 heat sink; topology optimization; data-driven optimization; computational fluid dynamics; experimental validation

Share and Cite

MDPI and ACS Style

Busqué, R.; Bossio, M.; Fabregat, R.; Bonada, F.; Maicas, H.; Pijuan, J.; Brigido, A. Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design. Energies 2025, 18, 2801. https://doi.org/10.3390/en18112801

AMA Style

Busqué R, Bossio M, Fabregat R, Bonada F, Maicas H, Pijuan J, Brigido A. Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design. Energies. 2025; 18(11):2801. https://doi.org/10.3390/en18112801

Chicago/Turabian Style

Busqué, Raquel, Matias Bossio, Raimon Fabregat, Francesc Bonada, Héctor Maicas, Jordi Pijuan, and Albert Brigido. 2025. "Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design" Energies 18, no. 11: 2801. https://doi.org/10.3390/en18112801

APA Style

Busqué, R., Bossio, M., Fabregat, R., Bonada, F., Maicas, H., Pijuan, J., & Brigido, A. (2025). Hybrid CFD and Monte Carlo-Driven Optimization Approach for Heat Sink Design. Energies, 18(11), 2801. https://doi.org/10.3390/en18112801

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