79 citations · 128 across the 10 of their papers we have counts for
10 papers
Effect of externally applied resonant magnetic perturbations on resistive tearing modes
Qiming Hu, Q. Yu, Bo Rao +3
Static resonant magnetic perturbations (RMPs) generated by saddle coil current have been applied in J-TEXT tokamak experiments in order to study their effects on tearing mode insta…
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…
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…
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…
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…
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…
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…
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…
MHD analysis on the physical designs of CFETR and HFRC
Ping Zhu, Li Li, Yu Fang +32
The China Fusion Engineering Test Reactor (CFETR) and the Huazhong Field Reversed Configuration (HFRC), currently both under intensive physical and engineering designs in China, ar…
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…