标题： 神经等离子体ODE中输运和辐射的敏感性分析 显示英文标题

标题： Sensitivity Analysis of Transport and Radiation in NeuralPlasmaODE for ITER Burning Plasmas

摘要： 理解关键物理参数如何影响燃烧等离子体行为对于ITER的可靠运行至关重要。 在本工作中，我们将NeuralPlasmaODE，一种基于神经常微分方程的多区域、多时间尺度模型，扩展以对ITER等离子体中的输运和辐射机制进行敏感性分析。 计算了核心和边缘温度和密度相对于输运扩散率、电子回旋辐射（ECR）参数、杂质分数和离子轨道损失（IOL）时间尺度的归一化敏感性。 分析聚焦于ITER感应场景训练后的名义模型周围的扰动。 结果突出了磁场强度、安全因子和杂质含量对能量约束的主要影响，同时也揭示了温度依赖的输运如何促进自调节行为。 这些发现展示了NeuralPlasmaODE在燃烧等离子体环境中的预测建模和场景优化中的实用性。 显示英文摘要

摘要： Understanding how key physical parameters influence burning plasma behavior is critical for the reliable operation of ITER. In this work, we extend NeuralPlasmaODE, a multi-region, multi-timescale model based on neural ordinary differential equations, to perform a sensitivity analysis of transport and radiation mechanisms in ITER plasmas. Normalized sensitivities of core and edge temperatures and densities are computed with respect to transport diffusivities, electron cyclotron radiation (ECR) parameters, impurity fractions, and ion orbit loss (IOL) timescales. The analysis focuses on perturbations around a trained nominal model for the ITER inductive scenario. Results highlight the dominant influence of magnetic field strength, safety factor, and impurity content on energy confinement, while also revealing how temperature-dependent transport contributes to self-regulating behavior. These findings demonstrate the utility of NeuralPlasmaODE for predictive modeling and scenario optimization in burning plasma environments.