Santhanakrishnan, Mani Sekara, Tilford, Tim ORCID: 0000-0001-8307-6403 and Bailey, Chris ORCID: 0000-0002-9438-3879 (2021) Multi-objective NSGA-II based shape optimisation of the cross-sectional shape of passively cooled heat sinks. International Journal of Numerical Methods for Heat and Fluid Flow, 32 (3). pp. 1025-1045. ISSN 0961-5539 (doi:https://doi.org/10.1108/HFF-10-2020-0656)

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Abstract

Purpose
The purpose of the study is to optimise the cross-sectional shape of passively cooled horizontally mounted pin-fin heat sink for higher cooling performance and lower material usage.

Design/methodology/approach
Multi-objective shape optimisation technique is used to design the heat sink fins. Non-dominated sorting genetic algorithm (NSGA-II) is combined with a geometric module to develop the shape optimiser. High-fidelity computational fluid dynamics (CFD) is used to evaluate the design objectives. Separate optimisations are carried out to design the shape of bottom row fins and middle row fins of a pin-fin heat sink. Finally, a computational validation was conducted by generating a three-dimensional pin-fin heat sink using optimised fin cross sections and comparing its performance against the circular pin-fin heat sink with the same inter-fin spacing value.

Findings
Heat sink with optimised fin cross sections has 1.6% higher cooling effectiveness than circular pin-fin heat sink of same material volume, and has 10.3% higher cooling effectiveness than the pin-fin heat sink of same characteristics fin dimension. The special geometric features of optimised fins that resulted in superior performance are highlighted. Further, Pareto-optimal fronts for this multi-objective optimisation problem are obtained for different fin design scenarios.

Originality/value
For the first time, passively cooled heat sink’s cross-sectional shapes are optimised for different spatial arrangements, using NSGA-II-based shape optimiser, which makes use of CFD solver to evaluate the design objectives. The optimised, high-performance shapes will find direct application to cool power electronic equipment.

Item Type:	Article
Additional Information:	‘Copyright © 2021, Emerald Publishing Limited. This AAM is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher.’
Uncontrolled Keywords:	heat sink design, genetic algorithm, shape optimisation, natural convection, CFD
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Centre for Numerical Modelling & Process Analysis (CNMPA) Faculty of Engineering & Science > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Mechanics & Reliability Group (CMRG) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	07 Jul 2022 14:09
URI:	http://gala.gre.ac.uk/id/eprint/32281

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