Design of a multi-scale cylindrical porous fin based on constructal theory

Porous fin (PF) has obvious advantages in heat dissipation, so it is necessary to analyze and optimize its performance. In this paper, a multi-scale cylindrical porous fin (PF) model is built. Firstly, the fin length and height ratio are chosen as the optimization variables, constructal design is conducted with the objective of complex function (CF) composed of maximum temperature difference (MTD) and pumping power consumption (PPC). Then, an artificial neural network (ANN) model is established by using data samples, and multi-objective optimization (MOO) is performed using the NSGA-II method. The findings indicated that the optimal length and height ratio of the fin are 4.763 mm and 1.017 under the conditions that the total PF envelope volume and PF-material volume are fixed. The CF is reduced by 51.0% compared with that before optimization. The multi-scale cylindrical porous fin with different heights is superior to the single-scale one with equal height. For MOO, the lowest deviation index obtained by TOPSIS or LINMAP decision-making strategy (DMS) is 0.258. For this case, the MTD is reduced by 81.9%, and the PPC is reduced by 18.7%. Therefore, the relevant optimal structure herein can be used as the optimal design solution for the multi-scale cylindrical porous fin.