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arXiv 2603.25751physics.plasm-phphysics.app-ph
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融合反应堆中性子燃料循环建模工作流程

Physics-informed tritium fuel cycle modelling workflow for fusion reactors

Massachusetts Institute of Technology(麻省理工学院);United Kingdom Atomic Energy Authority(英国原子能管理局)

Rémi Delaporte-Mathurin, Ross MacDonald, James Dark, Milan Rother, Tasnim Zulfiqar, Kevin B. Woller

AI总结:

本文提出一种基于开源PathSim/PathView平台的多保真度物理引导框架,用于融合反应堆中性子燃料循环建模。通过三种互补的建模方法,结合零维停留时间模型、中间保真度组件模型和高保真度多维中性子传输模型,实现了对燃料循环的系统级描述和验证。

摘要:

本文提出了一种基于开源PathSim/PathView平台的多保真度、物理引导的中性子燃料循环建模框架。在统一的动态模拟环境中,展示了三种互补的建模方法。首先,使用零维停留时间模型重现ARC类聚变发电厂的燃料循环行为,提供系统级描述。其次,开发了基于耦合一维常微分方程的中间保真度组件模型,用于描述液态金属气泡列管反应器中的中性子质量传输,并在整合到完整燃料循环前验证了文献数据。最后,使用有限元代码FESTIM实现的高保真度多维中性子传输模型直接耦合到系统模型中,使多维效应、材料界面和复杂传输现象得以包含。本文展示了如何在单一开源框架内一致地结合不同物理保真度的燃料循环组件。该方法使燃料循环分析更加物理基础化,同时保留了系统级研究所需的灵活性,并为未来与中子学、流体动力学和替代建模工具的集成提供了基础。

英文摘要:

In this work, we present a multi-fidelity, physics-informed framework for tritium fuel cycle modelling based on the open-source PathSim/PathView platform. Three complementary modelling approaches are demonstrated within a unified dynamic simulation environment. First, a zero-dimensional residence time model is used to reproduce the fuel cycle behaviour of an ARC-class fusion power plant, providing a baseline system-level description. Second, an intermediate-fidelity component model based on coupled one-dimensional ordinary differential equations is developed to describe tritium mass transfer in a liquid metal bubble column reactor and validated against published literature before integration into the full fuel cycle. Finally, high-fidelity multi-dimensional tritium transport models implemented using the finite element code FESTIM are coupled directly to the system model, enabling the inclusion of multi-dimensional effects, material interfaces, and complex transport phenomena. This work demonstrates how fuel cycle components of varying physical fidelity can be combined consistently within a single, open-source framework. The proposed approach enables more physically grounded fuel cycle analyses while retaining the flexibility required for system-level studies and provides a foundation for future integration with neutronics, fluid dynamics, and surrogate modelling tools.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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