A data-driven multi-physics coupling analysis method for multi-objective optimization design of an innovative heat pipe reactor core

Heat pipe cooled reactors have been developed more than 60 years, primarily utilizing ceramic fuels such as UO₂ and UN. However, the inherent characteristics of ceramic fuels impose limitations on the power density improvement of the heat pipe reactor core. In response to this challenge, an innovative conceptual design of a heat pipe reactor core with U-50Zr metallic fuel is proposed in this study. When addressing the multi-objective, multi-parameter and multi-physics coupling design challenges of heat pipe reactor cores, it is essential to introduce an efficient design and optimization method based on data-driven multi-physics coupling and multi-objective optimization analysis. Therefore, a three-dimensional multi-physics coupling analysis code is developed employing Matlab, OpenMC, and COMSOL. To enhance computational efficiency, the neural network surrogate models are established to replace the original code. Additionally, NSGA-II is utilized to obtain the optimal core design schemes, focusing on the objectives of higher power density of the core and lower fuel enrichment. Finally, in the results of the Pareto front, the detailed multi-physics coupling analyses are studied on two different core design schemes characterized by lower fuel enrichment and higher power density of the core, respectively. The design scheme with high power density features lower peak temperatures and lower peak stresses. In contrast, the design scheme with low enrichment provides a more uniform power distribution and greater backup reactivity. Both design schemes satisfy the operational requirements for a ten-year lifecycle, with temperatures and stresses remaining within the safety limits. This demonstrates the effectiveness of the proposed design approach and the analytical code. This study provides a reference for the design and multi-objective optimization of the heat pipe reactor core with U-50Zr metallic fuel and establishes a foundation for future transient optimization efforts.