Intelligent optimization of horizontal fins to improve the melting performance of phase change materials in a square cavity with isothermal vertical wall

A new combination mode of genetic algorithm (GA) and computational fluid dynamics (CFD) is proposed to solve optimization problems of fins for the enhancement of solid-liquid phase change heat transfer performance. In this optimization problem, some horizontal straight fins are installed on a vertical wall of a two-dimensional square cavity filled with PCM. The total cross-sectional area of fins is set as constraint, and the number, location and length/thickness of fins are selected as variables. The effect of natural convection on the melting characteristic of PCM is considered. The optimization results showed that fin length should be as long as possible and the fins should be arranged uniformly if the fin thickness is free. The existence of natural convection may slightly move fin downward to shorten the total melting time and increase the thermal energy storage rate. When the fin thickness is limited, the optimal number of fins depends on the total length of fins. One fin is suggested when the total length is smaller than 1.3, two fins when between 1.3 and 2.6, three fins when between 2.6 and 3.6, and four fins when greater than 3.6. Within the parameter range in this study, the thermal conductivity of fin material and fin thickness have ignorable effects on the critical values of total length, while the effects of natural convection should not be neglected. The critical length will increase with the increase of the Rayleigh number.

Automated summary

A new combination mode of genetic algorithm and computational fluid dynamics is proposed to optimize fins for solid-liquid phase change heat transfer enhancement. The study suggests that longer and uniformly arranged fins are optimal, and the presence of natural convection can improve melting time and thermal energy storage rate.