机载电子设备复合微通道液冷板智能优化设计 流动控制预热管理专栏

  • 张同勇 ,
  • 曾萌祥 ,
  • 陈强 ,
  • 费庆国 ,
  • 张大海
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  • 东南大学

收稿日期: 2025-11-03

  修回日期: 2026-02-02

  网络出版日期: 2026-02-09

基金资助

国家自然科学基金;国家自然科学基金;国家自然科学基金;国家自然科学基金;国家自然科学基金;江苏省自然科学基金;中国科协青年人才托举工程

Intelligent optimization design of composite microchannel liquid cold plate for airborne electronic devices

  • ZHANG Tong-Yong ,
  • ZENG Meng-Xiang ,
  • CHEN Qiang ,
  • FEI Qing-Guo ,
  • ZHANG Da-Hai
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Received date: 2025-11-03

  Revised date: 2026-02-02

  Online published: 2026-02-09

摘要

随着机载电子器件在性能与集成度上的进步,传统微通道散热器已难以满足其日益增长的散热需求。为此,围绕新型复合扰流结构微通道冷板,建立了基于神经网络的性能预示代理模型,并将其与NSGA-II算法相结合开展多目标优化研究,以进一步提升冷板综合性能。通过SHAP法揭示了影响冷板性能的主要因素,并基于熵权TOPSIS决策法获得了冷板最优无量纲设计参数。结果表明:神经网络能够充分学习和掌握冷板特征与性能间的复杂映射关系,具备较好的拟合精度和预测能力,最大平均绝对误差仅为0.383;代理模型大幅加速了优化进程,并保证了优化结果的可靠性,最大误差仅为6.34%;相较于原设计,所得最优冷板的平均努塞尔数和综合换热因子分别达70.755和2.223,综合性能提升了9.2%。

本文引用格式

张同勇 , 曾萌祥 , 陈强 , 费庆国 , 张大海 . 机载电子设备复合微通道液冷板智能优化设计 流动控制预热管理专栏[J]. 航空学报, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2026.33030

Abstract

With the improvements in performance and integration of onboard electronics, traditional microchannel heat sinks (MCHs) are inadequate for the escalating thermal management requirements. A surrogate model for MCH with turbulence-promoting structures is established based on neural network. Combined with NSGA-II, the surrogate is employed to conduct multi-objective optimization. The primary factors governing thermal-hydraulic performance is identified by SHAP analysis. Additionally, the optimal nondimensional design parameters are obtained based on entropy-weighted TOPSIS. The results indicate that the neural network fully learns the complex mapping between features and performance, achieving good fitting and predictive ability, with a maximum mean absolute error of 0.383. The surrogate accelerates optimization process, with a maximum error of 6.34%. Compared with original design, the optimized MCH achieves an average Nusselt number of 70.755 and an overall performance factor (PEC) of 2.223, yielding a 9.2% improvement in comprehensive performance.

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