J
J-Text Team
Researcher at Huazhong University of Science and Technology
Publications - 43
Citations - 388
J-Text Team is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Tokamak & Resonant magnetic perturbations. The author has an hindex of 8, co-authored 38 publications receiving 220 citations.
Papers
More filters
Journal ArticleDOI
Plasma flows and fluctuations with magnetic islands in the edge plasmas of J-TEXT tokamak
K.J. Zhao,Yuejiang Shi,S.H. Hahn,Patrick Diamond,Ye Sun,Jun Cheng,Hai Liu,N. Lie,Zhipeng Chen,Yonghua Ding,Z.Y. Chen,Bo Rao,M. Leconte,J.G. Bak,Z.F. Cheng,Li Gao,X.Q. Zhang,Zhoujun Yang,Nengchao Wang,Lu Wang,W. Jin,L.W. Yan,J.Q. Dong,Ge Zhuang,J-Text Team +24 more
TL;DR: In this paper, the magnetic island effects on flows and turbulence were investigated using multiple Langmuir probe arrays on the edge plasmas of the J-TEXT tokamak.
Journal ArticleDOI
Hybrid neural network for density limit disruption prediction and avoidance on J-TEXT tokamak
Wei Zheng,F.R. Hu,M. Zhang,Z.Y. Chen,X.Q. Zhao,X.L. Wang,P.W. Shi,X. L. Zhang,X.Q. Zhang,Yinan Zhou,Y N Wei,Yichang Pan,J-Text Team +12 more
TL;DR: Wang et al. as discussed by the authors developed an artificial neural network for the prediction of density limit disruptions on the J-TEXT tokamak, which was improved from a simple multi-layer design to a hybrid two-stage structure.
Journal ArticleDOI
Tearing mode suppression by using resonant magnetic perturbation coils on J-TEXT tokamak
B. Rao,Y. H. Ding,Qiming Hu,W.F. Shi,X.Q. Zhang,Ming Zhang,X.S. Jin,J. Y. Nan,K.X. Yu,Ge Zhuang,J-Text Team +10 more
TL;DR: In this paper, a series of experiments on the interactions between external resonant magnetic perturbations (RMP) and plasmas has been conducted, using static RMP coils on the Joint Texas Experimental Tokamak.
Journal ArticleDOI
Reconstruction of the TEXT-U Tokamak in China
Zhuang Ge,Ding Yonghua,Zhang Ming,Yu Kexun,Zhang Xiaoqing,Wang Zhijiang,Hu Xiwei,Pan Yuan,J-Text Team +8 more
TL;DR: The joint TEXT/TEXT-U tokamak has been re-built up in Huazhong University of Science and Technology in China as mentioned in this paper, where all sub-systems, such as poloidal field (PF) and toroidal field power supplies, vacuum system, diagnostics systems etc, are successfully integrated into the routine operation.
Journal ArticleDOI
Disruption predictor based on neural network and anomaly detection on J-TEXT
TL;DR: Machine learning (ML) based disruption prediction needs disruptive shots and is a black box thus can not extrapolates to other devices and future large tokamaks will not be able to provide disruption samples to develop a ML based predictor.