Optimizing L-shaped heat pipes with partially-hybrid mesh-groove wicking structures

Abstract 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.