Multi-objective optimization of cryogenic propellant zero boil-off storage: Modeling, optimization method and performance enhancement

Cryocooler-based zero boil-off schemes are promising for long-term storage of cryogenic propellants. To date, no studies have addressed the fluid-thermal coupling between key components of the zero boil-off system, as well as the trade-offs among the cooling power, insulation performance and energy utilization efficiency. To predict and optimize the performance of a cryocooler-based zero-boil-off system, a systemic model integrating theoretical calculations and computational fluid dynamics was developed. Additionally, a multi-objective optimization method was designed based on a modified hyperplane generation approach and a self-adaptive crossover operator. The accuracy of the model was validated using the results of liquid nitrogen experiments from the literature. On the same computation platform, the proposed optimization method demonstrated superior capabilities in avoiding local optima and accelerating convergence compared with the original Non-dominated Sorting Genetic Algorithm-III: the temperature uniformity of the cold shield improved by at least 10.44 %, and the time cost was reduced by 32.25 %. In addition, conflicts were identified among the cooling power, temperature uniformity of the cold shield, and parasitic heat leakage, whereas the temperature uniformity showed a positive correlation with heat leakage through multilayer insulation. These findings provide guidelines for the multi-objective design of cryogenic propellant storage systems for future space missions.