AI 中文总结
本研究开发耦合OpenMC、OpenFOAM与FESTIM的多物理场框架，模拟ARC级聚变反应堆包层氚输运，得到氚 inventory、输运机制等关键结果，为相关高保真分析提供基础。
AI 中文摘要
准确预测熔盐增殖包层中的氚行为对于ARC级聚变反应堆的设计与安全运行至关重要。本研究提出了一种完全开源的组件级多物理场框架，用于模拟ARC浸没式液体包层中的氚输运。该框架使用OpenMC、OpenFOAM和FESTIM耦合中子输运、热工水力及氢同位素输运，利用专用工具实现求解器间空间分辨场的直接传递。假设入口浓度为零，稳态模拟预测总氚 inventory 约为243 mg，包层在约30分钟内达到稳态氚 throughput，与之前系统级估计值处于同一数量级。结果表明，氚输运由湍流增强扩散主导，在流动停滞区存在强局域化，而在高湍流区积累减少。敏感性分析显示，预测的 inventory 主要受数值稳定格式控制，仅与湍流施密特数有适度依赖关系。所提出的工作流为ARC级增殖包层中氚输运的高保真分析提供了透明且可扩展的基础。
英文摘要
Accurate prediction of tritium behaviour in molten salt breeding blankets is essential for the design and safe operation of ARC-class fusion reactors. This work presents a fully open-source, component-scale multiphysics framework for modelling tritium transport in an ARC liquid immersion blanket. Neutron transport, thermal hydraulics, and hydrogen isotope transport are coupled using OpenMC, OpenFOAM, and FESTIM, leveraging dedicated tools enabling direct transfer of spatially resolved fields between solvers. Assuming a zero inlet concentration, steady-state simulations predict a total tritium inventory of approximately 243 mg, with the blanket reaching steady-state tritium throughput within approximately 30 min, which is of a similar order to previous system-level estimates. The results show that tritium transport is dominated by turbulence-enhanced diffusion, with strong localisation in flow stagnation regions and reduced accumulation in highly turbulent zones. Sensitivity analyses indicate that predicted inventories are governed primarily by the numerical stabilisation scheme, with only a modest dependence on the turbulent Schmidt number. The proposed workflow provides a transparent and extensible basis for high-fidelity analysis of tritium transport in ARC-class breeding blankets.
