THERMAL SCIENCE

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Meixia Jiang

,

Zhongliang Pan

OPTIMIZATION OF MICRO-CHANNEL HEAT SINK BASED ON GENETIC ALGORITHM AND BACK PROPAGATION NEURAL NETWORK

ABSTRACT
In order to efficiently solve the problem of optimization of the micro-channel heat sink, an optimization strategy combining intelligent algorithms and CFD was proposed. The micro-channel heat sink with the trapezoidal cavity and solid/slotted oval pins was proposed to enhance heat transfer. The aspect ratio, distance from the center of the oval pin to the center of the cavity, and slot thickness were design variables. The thermal resistance and pumping power of the micro-channel heat sink were objective functions. Within the selected range of design variables, thirty groups of uniformly sampled sample points were obtained by the Latin hypercube experiment. The 3-D model was established by SOLIDWORKS software, and the numerical simulation was carried out by using FLUENT soft-ware. The genetic algorithm optimized back propagation neural network to construct the prediction model, and the simulated data of Latin hypercube sampling were trained to obtain the non-linear mapping relationship between design variables and objective functions. The optimal combination of structural parameters of the micro-channel heat sink was obtained by optimization of the genetic algorithm, which was verified by numerical simulation. The results show that the optimization scheme was suitable for getting the optimal value of the structural parameters of the micro-channel heat sink, which provided a reference for the optimal design of the micro-channel heat sink.
KEYWORDS
micro-channel heat sink, pumping power, thermal resistance, Latin hypercube sampling, GA-BP neural network, genetic algorithm
PAPER SUBMITTED: 2022-03-07
PAPER REVISED: 2022-04-01
PAPER ACCEPTED: 2022-08-11
PUBLISHED ONLINE: 2022-09-10
DOI REFERENCE: https://doi.org/10.2298/TSCI220307121J
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2023, VOLUME 27, ISSUE Issue 1, PAGES [179 - 193]
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Optimization of micro-channel heat sink based on genetic algorithm and back propagation neural network

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence