activity
20182025
most citedIDP-PGFE: An Interpretable Disruption Predictor based on Physics-Guided Feature Extraction

25 citations · 55 across the 11 of their papers we have counts for

collaborators

11 papers

physics.plasm-ph2025

Effects of turbulence spreading and symmetry breaking on edge shear flow during sawtooth cycles in J-TEXT tokamak

Xiaoguan Ding, Kaijun Zhao, Yaoyu Xie +7

Sawtooth oscillations can trigger off heat and turbulence pulses that propagate into the edge plasma, and thus enhancing the edge shear flow and inducing a transition from low conf…

physics.plasm-ph2025

Healing of the edge magnetic island in the island divertor configuration on J-TEXT

Zhangrong Hou, Song Zhou, Nengchao Wang +18

The phenomena of island healing and configuration transition induced by high-power electron cyclotron resonance heating (ECRH) have been investigated in the island divertor configu…

physics.plasm-ph2024

Adaptive Anomaly Detection Disruption Prediction Starting from First Discharge on Tokamak

Xinkun Ai

Plasma disruption presents a significant challenge in tokamak fusion, where it can cause severe damage and economic losses. Current disruption predictors mainly rely on data-driven…

physics.plasm-ph2023

Extraction of n = 0 pick-up by locked mode detectors based on neural networks in J-TEXT

Chengshuo Shen, Jianchao Li, Yonghua Ding +10

Measurement of locked mode (LM) is important for the physical research of Magnetohydrodynamic (MHD) instabilities and plasma disruption. The n = 0 pick-up need to be extracted and…

physics.plasm-ph2023★ 6 cited

Cross-Tokamak Deployment Study of Plasma Disruption Predictors Based on Convolutional Autoencoder

Xinkun Ai, Wei Zheng, Ming Zhang +12

In the initial stages of operation for future tokamak, facing limited data availability, deploying data-driven disruption predictors requires optimal performance with minimal use o…

physics.plasm-ph2023★ 1 cited

Critical roles of edge turbulent transport in the formation of high-field-side high-density front and density limit disruption in J-TEXT tokamak

Peng Shi, Yuhan Wang, Li Gao +16

This article presents an in-depth study of the sequence of events leading to density limit disruption in J-TEXT tokamak plasmas, with an emphasis on boudary turbulent transport and…

physics.plasm-ph2023★ 3 cited

Validation of the plasma-wall self-organization model for density limit in ECRH-assisted start-up of Ohmic discharges on J-TEXT

Jiaxing Liu, Ping Zhu, Dominique Franck Escande +14

A recently developed plasma-wall self-organization (PWSO) model predicts a significantly enhanced density limit, which may be attainable in tokamaks with ECRH-assisted ohmic startu…

physics.plasm-ph2023★ 11 cited

Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection

Xinkun Ai, Wei Zheng, Ming Zhang +12

The full understanding of plasma disruption in tokamaks is currently lacking, and data-driven methods are extensively used for disruption prediction. However, most existing data-dr…

physics.plasm-ph2022★ 2 cited

Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor

Wei Zheng, Fengming Xue, Ming Zhang +12

Predicting disruptions across different tokamaks is a great obstacle to overcome. Future tokamaks can hardly tolerate disruptions at high performance discharge. Few disruption disc…

physics.plasm-ph2022★ 25 cited

IDP-PGFE: An Interpretable Disruption Predictor based on Physics-Guided Feature Extraction

Chengshuo Shen, Wei Zheng, Yonghua Ding +10

Disruption prediction has made rapid progress in recent years, especially in machine learning (ML)-based methods. Understanding why a predictor makes a certain prediction can be as…

physics.plasm-ph2018★ 7 cited

Observation of non-local effects in ion transport channel in J-TEXT plasmas

Yuejiang Shi

In cold pulse experiments in J-TEXT, the ion transport shows similar non-local response as the electron transport channel. Very fast ion temperatures decreases are observed in the…