The solidification characteristics of PCM heat exchangers with bionic fins and nanoparticles for by a compound method of sensitivity analysis, multi-objective optimization and evaluation

This study investigates the influence of an innovative biomimetic fin enhanced with nanoparticles on the solidification behavior of phase change materials. A sensitivity analysis of the biomimetic fin's design parameters was performed using Response Surface Methodology (RSM), leading to the development of a predictive correlation. Multi-objective optimization algorithms, including Non-dominated Sorting Genetic Algorithm-II (NSGA-II), NSGA-III, and Multi-objective Particle Swarm Optimization (MOPSO), were employed to identify Pareto optimal sets and determine the most advantageous design variables. Additionally, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was applied to the Pareto optimal set for multi-criteria ranking, ultimately identifying the most optimal solution and corresponding parameters. The results indicate that, based on sensitivity analysis, the fin length and width significantly affect the complete solidification time and heat transfer rate, respectively. The NSGA-III Pareto optimal set demonstrated improvements in heat transfer rate ranging from 62.17 % to 70.13 %, 32.5 % to 39 %, and 30.61 % to 37.02 % compared to rectangular, tree-like, and single-layer perforated tree fins, respectively, while reducing complete solidification time by 59.87 % to 60.23 %, 16.01 % to 16.76 %, and 15.04 % to 15.8 %. Moreover, structural optimization outperformed nanoparticle-based heat transfer enhancement, demonstrating the effectiveness of enhanced thermal conductivity and convective synergy.