arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~

托卡马克磁控制的逆Grad-Shafranov神经网络方法

An Inverse Grad-Shafranov Neural Network Approach to Tokamak Magnetic Control

Allen M. Wang, Adriano Mele, Cosmas Heiß, Cristian Galperti, Zander Keith, Alessandro Pau, Antoine Merle, Olivier Sauter, Daniel Gonzalez Castiñeiras, Francesco Carpanese, Federico Felici, Mark Dan Boyer, Cristina Rea, TCV Team, EUROfusion Tokamak Exploitation Team

arXiv 2608.23976首次发表:更新:

发表机构

MIT Plasma Science and Fusion Center; École Polytechnique Fédérale de Lausanne (EPFL); Google DeepMind; Fusionality SA; Commonwealth Fusion Systems(麻省理工学院等离子体科学与聚变中心; 洛桑联邦理工学院; 谷歌DeepMind; Fusionality SA; 联邦聚变系统)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

本文提出一种逆Grad-Shafranov神经网络方法,在TCV上实验验证其可实现高精度等离子体成形,减少对密集诊断的依赖,对未来聚变电厂运行有潜在价值。

AI 中文摘要

本文在托卡马克构型变量(TCV)上实验验证了一种实现高精度等离子体成形和新型实时适应性的托卡马克磁控制新方法。该方法的灵感来源于:在适当假设下,实时逆Grad-Shafranov求解器可近似为等离子体边界调节的最优控制策略。基于此,研究人员开发了一种控制架构,其中经典控制器用于执行运行约束,而快速代理模型则提供从期望等离子体边界到极向场线圈电流的实时逆映射。TCV上的实验结果表明,相较于标准放电准备程序,该方法可改善等离子体成形效果(尽管未采用显式实时形状反馈),同时支持对异步事件的灵活响应。研究显示,单个网络可在一系列等离子体磁构型上提供令人满意的性能;通过自适应打击点运动和响应实时触发的提前终止,该方法在模拟中及部分实验中验证了实时适应性。这些结果表明,该方法为磁控制架构提供了可行路径,可在保持高精度等离子体成形的同时减少对密集诊断覆盖的依赖,对未来聚变电厂运行具有潜在意义。

英文摘要

A new approach to tokamak magnetic control enabling high-precision plasma shaping and novel real-time adaptability is experimentally demonstrated on the Tokamak a Configuration Variable (TCV). The method is motivated by the insight that, under appropriate assumptions, a real-time inverse Grad-Shafranov solver approximates an optimal control policy for plasma boundary regulation. Building on this, a control architecture is developed in which classical controllers enforce operational constraints while a fast surrogate model provides a real-time inverse mapping from the desired plasma boundary to Poloidal Field Coil currents. Experimental results on TCV demonstrate improved plasma shaping with respect to the standard discharge preparation procedure --- albeit without explicit real-time shape feedback --- while enabling flexible response to asynchronous events. It is shown that a single network provides satisfactory performance across a range of plasma magnetic configurations. Real-time adaptivity is demonstrated in simulation, and partially in experiment, through adaptive strike point motion and early termination in response to a real-time trigger. These results suggest a viable path toward magnetic control architectures that reduce reliance on dense diagnostic coverage while maintaining high-accuracy plasma shaping, with potential relevance for future fusion power plant operation.

论文原文

arXiv 摘要页 · PDF 原文 · HTML 原文

↑