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首页> 外文期刊>International Journal of Heat and Mass Transfer >Optimizing L-shaped heat pipes with partially-hybrid mesh-groove wicking structures
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Optimizing L-shaped heat pipes with partially-hybrid mesh-groove wicking structures

机译：优化具有部分混合网槽芯芯结构的L形热管

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In this study, a novel type of partially-hybrid mesh-groove wicking structures have been proposed to enhance L-shaped copper-ethanol heat pipes. Enhancements come from two aspects: (a) the enhanced evaporation via a hybrid mesh-groove wicking structure and (b) the promoted condensation by managing the unwanted flooding in the condensation section. Experimental studies have been conducted to optimize the hybrid mesh-groove wicking structures. Three types of wicking structures including grooves, partially-hybrid mesh-grooves, and fully-hybrid mesh-grooves are studied and compared. The results show that the heat pipe with partially-hybrid wicking structures substantially outperforms heat pipes with the other two types of wicking structures. The thermal resistance of the heat pipe with a partially-hybrid wicking structure has been reduced up to 57.4% compared to that of the heat pipe with axially grooves. Moreover, in this study, in order to optimize the wicking structures, the effect of mesh-layers number and charging ratio on the L-shaped partially-hybrid mesh-groove wicked heat pipe (LPHHP) has been investigated. The optimal mesh-layer numbers of the LPHHP are found to be 1-2 layers. More importantly, instead of a specific value for a given heat pipe in existing studies, this study shows that the optimal charging ratio is actually a region, which highly depends on heat loads. However, it is extremely challenging to optimize a heat pipe with such a complicated wicking structure theoretically or numerically due to the involved complex two-phase heat transfer. Thus, a regression analysis method in machine learning is proposed to optimize the charging ratio of the LPHHP.
机译：在该研究中，已经提出了一种新型的部分混合网槽芯芯结构，以增强L形铜 - 乙醇热管。增强来自两个方面：（a）通过混合网槽芯芯结构和（b）通过管理冷凝部分中的不需要的洪水来增强促进的冷凝。已经进行了实验研究以优化混合网槽芯芯结构。研究了三种类型的芯吸结构，包括凹槽，部分混合网槽和完全混合网格凹槽。结果表明，具有部分混合芯吸的热管结构基本上优于热管与其他两种芯吸结构。与具有轴向槽的热管的热管的热管的热阻已减少至57.4％。此外，在本研究中，为了优化芯吸结构，已经研究了对L形部分 - 混合网槽储存热管（LPHHP）的网状层数量和充电比的影响。 LPHHP的最佳网格层数是1-2层。更重要的是，本研究表明，该研究表明，最佳充电比实际上是一个高度取决于热负荷的区域。然而，在理论上或数量上通过所涉及的复杂的两相热传递来优化具有这种复杂的芯吸结构的热管来极具挑战性。因此，提出了一种机器学习中的回归分析方法来优化LPHHP的充电比。

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