基于NSGA-Ⅱ算法的直流传导电磁泵多目标优化

doi:10.11896/cldb.24010163

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Abstract The thermal barrier problem of highly integrated chips and electronic devices has become a bottleneck restricting their intensive development, the problem of low boiling point, low thermal conductivity and susceptibility to boiling phase change of traditional water-cooling system can be effectively solved by utilizing DC conduction electromagnetic pump (DC-EMP) to drive the liquid metal for heat transfer and heat dissipation. In order to improve the efficiency of the DC-EMP, a Kriging model was developed. The length of the working area, channel width, channel height and input current were taken as the design variables, and pressure and efficiency were taken as the objective functions, the NSGA-Ⅱand TOPSIS method were used for the multi-objective optimization, and the initial scheme and optimization results were tested for external characteristics. The results show that the numerical simulation is in general agreement with the experimental results. The optimized DC-EMP has improved pressure and efficiency at design conditions by 32.72% and 8.85%, respectively, compared to the initial solution. The optimized average magnetic field density in the pump increased by about 36.58% and the distribution inhomogeneity decreased by about 19.36%. The relative velocity distribution of the fluid in the flow channel is more uniform, and the magnetohydrodynamic effect on the liquid metal flow is weakened. Based on the results of optimization, the installation of insulating plates in the flow channel parallel to the direction of flow can effectively reduce the spreading effect of the current and increase the effective current.

Key words： liquid metal DC conduction electromagnetic pump Kriging model genetic algorithm

Published: 10 May 2025 Online: 2025-04-28

CLC number:

TH35

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	Articles by authors
	CHEN Guanci
	YANG Jin
	ZHANG Wenbin
	YANG Zhaolin
	CHEN Yonghua

Cite this article:

CHEN Guanci,YANG Jin,ZHANG Wenbin, et al. Multi-objective Optimization of DC Conduction Electromagnetic Pump Based on NSGA-Ⅱ Algorithm[J]. Materials Reports, 2025, 39(9): 24010163-7.

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https://www.mater-rep.com/EN/10.11896/cldb.24010163 OR https://www.mater-rep.com/EN/Y2025/V39/I9/24010163

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