标题： 一种等离子体粒子和能量传输的广义多节点模型 显示英文标题

标题： A Generalized Multinodal Model for Plasma Particle and Energy Transport

摘要： 我们提出了一种广义的多节点模型，用于模拟环形等离子体配置中的粒子和能量输运，该模型旨在支持燃烧等离子体分析和反应堆尺度建模。 与固定节点模型不同，此公式允许任意数量的节点，为与核心-边缘或核心-梯度区模拟的耦合提供了更大的灵活性。 该模型通过在环形壳层节点上对连续性和能量守恒方程进行体积平均，推导出每种等离子体物种的节点平衡方程。 粒子和能量输运项以节点间通量的形式表示，分别通过粒子密度和温度的线性扩散定律与径向梯度相关联。 由此产生的输运贡献通过有效粒子和能量输运时间来表征，这些时间明确地根据节点几何结构和扩散率得出。 这种广义框架促进了在简化的或综合的等离子体模拟中径向输运动力学的高效模块化实现，并且与数据驱动方法如NeuralPlasmaODE兼容，可用于从实验数据进行模型校准和推断。 显示英文摘要

摘要： We present a generalized multinodal model for simulating particle and energy transport in toroidal plasma configurations, developed to support burning plasma analysis and reactor-scale modeling. Unlike fixed-node models, this formulation allows an arbitrary number of nodes, offering increased flexibility for coupling with core-edge or core-pedestal simulations. The model derives nodal balance equations for each plasma species by volume-averaging the continuity and energy conservation equations across toroidal shell nodes. Particle and energy transport terms are expressed in terms of internodal fluxes, linked to radial gradients via linear diffusion laws for particle density and temperature, respectively. The resulting transport contributions are characterized through effective particle and energy transport times, derived explicitly in terms of nodal geometry and diffusivities. This generalized framework facilitates efficient, modular implementation of radial transport dynamics in reduced-order or integrated plasma simulations, and is compatible with data-driven approaches such as NeuralPlasmaODE for model calibration and inference from experimental data.