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Multi-objective NSGA-II based shape optimisation of the cross-sectional shape of passively cooled heat sinks

Multi-objective NSGA-II based shape optimisation of the cross-sectional shape of passively cooled heat sinks

Santhanakrishnan, Mani Sekara, Tilford, Timothy ORCID: 0000-0001-8307-6403 and Bailey, Christopher 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. ISSN 0961-5539 (In Press)

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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 3D 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 which 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
Uncontrolled Keywords: Heat sink design, Genetic algorithm, Shape optimisation, Natural convection, CFD
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Centre for Numerical Modelling & Process Analysis (CNMPA)
Faculty of Liberal Arts & Sciences > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Mechanics & Reliability Group (CMRG)
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Related URLs:
Last Modified: 28 Apr 2021 20:34
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/32281

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