Multiobjective Optimization Framework for Breeding Blanket Design With Remote Maintenance Consideration

To ensure the continued and stable operation of the nuclear fusion device, the blanket must be periodically replaced due to material consumption. The presence of highly radioactive and extreme temperature environment makes remote operation the only feasible method for blanket maintenance. However, the heavy self-weight of current blanket designs poses significant challenges for remote maintenance (RM). Therefore, a structural redesign of the blanket is essential to improve the feasibility and efficiency of remote operations. Meanwhile, the tritium breeding capability and heat transfer performance of the blanket are critical physical indicators that directly affect the energy output of the fusion device and must be considered during the redesign phase. In this work, we propose a multiobjective optimization framework that balances both the physics availability of the blanket and the engineering feasibility of the blanket maintenance. A parametric modeling approach for blanket geometry is proposed to enable flexible adaptation of the blanket shape under different design requirements. To demonstrate the framework, a case study on the RM optimization is conducted, achieving up to 35% reduction in lifting torque through blanket geometric optimization, thereby providing robust support for RM and offering useful insights for an overall systematic analysis of the blanket design.