Multi-objective optimization on bionic fractal structure for heat exchanging of two fluids by genetic algorithm

Abstract

Numerous industrial processes involve heat exchange, and the efficiency of energy usage depends heavily on the effectiveness of this exchange. Thermal structure is a critical factor that influences the process of heat transfer. The bionic fractal structure has been heavily researched due to its ability to provide a more uniform flow distribution and improved heat transfer performance. An iterative approach to determining the central wall temperature is suggested for heat transfer between two fluids with varying mass flow rates and physical features. A bionic fractal heat transfer model for two fluids was developed, and the features of the bionic fractal heat transfer structure with supercritical carbon dioxide (supercritical CO2) and H2O were expounded. Furthermore, the variation of heat transfer performance with parameters was analyzed comprehensively. A method for the optimization and design of a bionic fractal heat transfer structure using two fluids was also provided, and the index of heat transfer performance was found to have the best value for various structural factors. The multi-objective optimizations of the bionic fractal heat transfer structure were carried out by a genetic algorithm, and the results showed a 15% reduction in power consumption for the optimized heat transfer structure, a 2.4% increase in heat transfer, and an improvement in the index of heat transfer performance by 17%.