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

Date

2021-07-16

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Publisher

Emerald

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Article

ISSN

0961-5539

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Citation

Santhanakrishnan MS, Tilford T, Bailey C. (2022) 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, Volume 32, Issue 3, July 2022, pp. 1025-1045

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.

Description

Software Description

Software Language

Github

Keywords

Natural convection, Shape optimisation, Genetic Algorithm, Heat sink design, CFD

DOI

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Attribution-NonCommercial 4.0 International

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