Resistance reduction of vapor flow in ultra-thin vapor chambers through support columns topological optimization

Abstract

Ultra-thin vapor chambers face the challenge that vapor diffusion flow resistance increases with decreasing thickness, leading to a sharp rise in overall thermal resistance. In the present study, a two-dimensional topology optimization framework based on the density method is developed for the shape design of single and multiple support columns, aimed at minimizing vapor flow resistance. Results demonstrate that at an inlet velocity of 13.3097 m/s, the topology-optimized quasi-elliptical single column achieves a 3.01% pressure drop reduction compared to a circular column of equal cross-sectional area. As the flow velocity increases, the optimal shape exhibits a larger aspect ratio, its geometric center shifts forward, and the pressure drop shows a linear relationship with velocity. Extending the optimized single-column shape to a multi-column model reduces the flow pressure drop by 8.08%, corresponding to a 1.48 K decrease in heat source temperature, yet the optimal design for a single column may not remain optimal in a multi-column flow field. Collaborative optimization of multiple columns reveals that reducing the pressure drop essentially seeks the shortest vapor flow path, minimizing low-pressure zones at the front and rear of the columns. The optimization lowers the average inlet-outlet pressure drop of double-row double-column support column models by 3.53%, with the reduction being more pronounced under high-velocity conditions. Under non-uniform incoming flow, the topology-optimized shapes exhibit clear flow-directing characteristics and adaptive behavior, achieving the lowest global pressure drop performance.