首页|Multi-objective optimization of a mini-channel heat sink with non-uniform fins using genetic algorithm in coupling with CFD models
Multi-objective optimization of a mini-channel heat sink with non-uniform fins using genetic algorithm in coupling with CFD models
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NSTL
Elsevier
Micro/mini-channel heat sinks (MCHS) have been extensively employed for heat dissipation under high heat flux conditions, and their performances are crucial for safe and stable operation. This study presents a multi-objective optimization work to reduce pressure drop Δp and thermal resistance θ for the MCHS with non-uniform fins in a staggered arrangement. Multi-objective genetic algorithm and computational fluid dynamics software were coupled to find the Pareto solutions with optimal fin lengths and longitudinal spacings. Compared with the initial MCHS with four uniform fins, Δp of solution Optimalθ and θ of OptimalΔp were respectively reduced by 13.62% and 10.24%. Meanwhile, Spearman's rank correlation coefficient was obtained to reveal the relationship between fin configurations and performances, which indicated that the front sparse and rear dense fin arrangements are beneficial in achieving high comprehensive performances. To fully utilize the pumping power, the upstream heat transfer performance was sacrificed, however, all the local maximum base temperatures were excellently controlled to ensure thermal resistance. Furthermore, a multi-criteria decision-making approach was applied to select the best compromise solution OptimalTOPSIS. Besides reducing Δp by 8.35% and θ by 6.13%, OptimalTOPSIS also reduced the material cost by 10.80% and improved the uniformity of base temperature by 2.18 K.
Best compromise solutionComputational fluid dynamicsMini-channel heat sinkMulti-objective optimizationNon-uniform fin configuration
Ge Y.、He Q.、Lin Y.、Yuan W.、Chen J.、Huang S.-M.
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Guangdong Provincial Key Laboratory of Distributed Energy Systems Guangdong Provincial Engineering Research Center of Distributed Energy Systems Dongguan University of Technology
NSTL
Elsevier
