図版検索トレンド wiki 日本の研究

© 2026 FUSIONPAPERS

About 法務情報

トップに戻る

Density regulation with disruption avoidance in next-generation tokamaks using a safe reinforcement learning-based controller

Sai Tej Paruchuri, Ian Ward, Nicholas Rist, Vincent Graber, June-Woo Juhn2025年7月Fusion Engineering and DesignIF 1.7 出版社

wiki

Plasma disruption

この論文にはまだAI要約がありません。

関連論文

Real-time feedback control of βp based on deep reinforcement learning on EAST

2024Plasma Physics and Controlled Fusion

Towards practical reinforcement learning for tokamak magnetic control

2024Fusion Engineering and Design

Enhancing deep reinforcement learning with integral action to control tokamak safety factor

2023Fusion Engineering and Design

Hybrid neural network for density limit disruption prediction and avoidance on J-TEXT tokamak

2018Nuclear Fusion

Developing disruption avoidance functions for the ITER plasma control system

2026Plasma Physics and Controlled Fusion

Balancing physics priors and data for disruption prediction in future tokamaks

2026Nuclear Fusion

First experimental results with the Current Limit Avoidance System at the JET tokamak

2013Fusion Engineering and Design

Prediction of density limit disruptions on the J-TEXT tokamak

2016Plasma Physics and Controlled Fusion

A numerical study of density limit mechanisms in tokamaks

1998Physics of Plasmas

Density limits in tokamaks

1997Physics of Plasmas