Optimizing heat transfer in phase change thermal energy storage systems: A bionic method using alveolar vessel fins and nanofluids

This paper investigates the enhanced heat transfer performance of a phase change thermal energy storage system (TES) using alveolar vessel-inspired fins and nano-fluid. Compared with traditional rectangular fins, alveolar vascular fins have better heat dissipation ability. The study utilizes computational fluid dynamics (CFD) to simulate and optimize the heat storage process. The results demonstrate that the 5 % Cu nanoparticles and water mixed nanofluid exhibits 27.63 % improvement in heat storage density compared to pure water. Furthermore, the heat transfer performance of nanofluid follows the trend Cu > CuO > Al2O3 > TiO2. The study also investigates the impact of heat transfer fluid (HTF) operating conditions, finding that an initial velocity of 0.25 m/s results in a 17 K increase in the average phase change material (PCM) temperature compared to 0.05 m/s. Finally, multi-objective optimization is conducted using response surface method and non-dominated sorting genetic algorithm II to determine the optimal parameters, heat storage capacity, PCM average temperature and kinetic energy values of 10.33 kJ, 492.19 K, and 2.25 mJ, respectively, corresponding to initial velocity 0.15 m/s of HTF, initial temperature 373.00 K of HTF, and volume fraction 4.41 % of nanoparticles in HTF. This simulation and multi-objective optimization method highlights the bionic inspiration design, and at the same time has certain reference significance for the multi-objective competitive design of nano-fluids in TES.