Multi-objective optimization of active cooling and compressive load-bearing performance of truss-cored sandwich panel using genetic algorithm

Sandwich panels with truss cores offer versatile capabilities, such as heat dissipation and load-bearing, making them promising options for multifunctional applications. However, optimizing thermal and mechanical performance often requires different structural parameters for the sandwich cores. Therefore, it is necessary to balance thermal and mechanical performance during structural design. In this study, a pyramid lattice-cored sandwich panel was evaluated under simultaneous thermal and pressure loads. The multifunctional design of the sandwich panel was optimized using the NSGA-II algorithm to enhance active cooling efficiency, load-bearing capacity, and lightweight index. The design variables included core parameters such as strut diameter, inclination angle, and core height. The active cooling performance of the sandwich panel was assessed using CFD simulation with the k-ω SST turbulence model. Meanwhile, the compressive load-bearing capacity and lightweight index were evaluated using theoretical relations. To validate the optimization results, forced convection experiments and quasi-static out-of-plane compression tests were conducted. From the Pareto solutions predicted by the NSGA-II algorithm, the optimal design point was identified. The predicted heat transfer coefficient and collapse strength of the optimal design were within 15 % and 6.3 %., respectively, of the experimental data. Compared to the initial design, the optimal design increased the heat transfer coefficient by 79.1 % and the collapse strength by 40.6 %, while maintaining nearly the same relative density.