Structural optimization of double-layer capillary wick in a cryogenic loop heat pipe system via genetic algorithm

Cryogenic loop heat pipes (CLHPs) are reliable and effective low-temperature heat transfer devices. The thermal transfer performance of a CLHP, which is dominated by the parameters of the evaporator capillary core, has not been well investigated. In this study, a comprehensive model combining a genetic algorithm with a system mathematical model was built to optimize the performance of CLHPs. The parameters of inner layer diameter, thermal conductivity of the inner layer, and porosity of the evaporator capillary core were considered in the optimization process. The maximum heat load under different evaporation temperature was proposed to evaluate the best performance of the CLHP. Results showed that when the thermal conductivity was 9.85 W/(m∙K), the porosity was 0.542, and the outer diameter of the inner capillary wick was 0.0084 m, the maximum heat load reached the highest value when the evaporation temperature was less than 85.5 K. When the evaporating temperature in the constraints of fitness function decreased to 82.5 K, the thermal conductivity decreased to 1.19 W/(m∙K), the porosity increased to 0.567, and the outer diameter of the inner capillary core was 0.0094 m. Above findings can be used as a guide for designing high-performance CLHPs to meet different functional requirements.