Multi-Objective Optimization on Bionic Fractal Structure for Heat Exchanging of Single Fluids by Genetic Algorithm

Abstract

The heat transfer process using a single-fluid cooling wall is widely used in various fields, including high-performance computers, solar panels, automotive power supplies, and aerospace engine protection. In high heat flux environments, thermal management has become a significant challenge, and enhancing heat transfer is crucial for effective thermal management. Although parallel microchannel heat transfer structures are a current research focus due to their compact structure and easy manufacturing, their uneven flow distribution is a key constraint hindering further development. Bionic fractal heat transfer structures have gained widespread attention due to their favorable flow uniformity, high efficiency, and low energy consumption. Currently, the structural design of biomimetic fractal heat transfer structures mostly employs Murray's law and its derived parameters. A thermal design program suitable for variable flow rate and physical properties is proposed and a model for a single fluid biomimetic fractal heat transfer structure is established. The heat transfer characteristics of fractal heat transfer structures were explained using supercritical CO2 as a heat transfer medium. The study comprehensively analyzed the influence of different design parameters of single-fluid biomimetic fractal heat transfer structures on heat transfer performance and provided a method for optimizing their design. The results showed that there exists an optimal value for heat transfer performance indicators under different structural design parameters. Genetic algorithms are applied to multi-objective optimize the structural parameters of biomimetic fractal heat transfer structures and the performance indicator is improved by 21.6%.

Keywords: Bionic fractal structure, Thermo-hydraulic performance, heat transfer enhancement, Genetic algorithm optimization, single-fluid cooling