Követés
Jinxiang Zhu
Jinxiang Zhu
E-mail megerősítve itt: mit.edu
Cím
Hivatkozott rá
Hivatkozott rá
Év
Overview of the SPARC tokamak
AJ Creely, MJ Greenwald, SB Ballinger, D Brunner, J Canik, J Doody, ...
Journal of Plasma Physics 86 (5), 865860502, 2020
4192020
MHD stability and disruptions in the SPARC tokamak
R Sweeney, AJ Creely, J Doody, T Fülöp, DT Garnier, R Granetz, ...
Journal of Plasma Physics 86 (5), 865860507, 2020
572020
Hybrid deep-learning architecture for general disruption prediction across multiple tokamaks
JX Zhu, C Rea, K Montes, RS Granetz, R Sweeney, RA Tinguely
Nuclear Fusion 61 (2), 026007, 2020
552020
Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks
J Zhu, C Rea, RS Granetz, ES Marmar, KJ Montes, R Sweeney, ...
Nuclear Fusion 61 (11), 114005, 2021
262021
A semi-supervised machine learning detector for physics events in tokamak discharges
KJ Montes, C Rea, RA Tinguely, R Sweeney, J Zhu, RS Granetz
Nuclear Fusion 61 (2), 026022, 2021
202021
Integrated deep learning framework for unstable event identification and disruption prediction of tokamak plasmas
JX Zhu, C Rea, RS Granetz, ES Marmar, R Sweeney, K Montes, ...
Nuclear Fusion 63 (4), 046009, 2023
142023
The root cause of disruptive NTMs and paths to stable operation in DIII-D ITER baseline scenario plasmas
L Bardoczi, NJ Richner, NC Logan, EJ Strait, CT Holcomb, J Zhu, C Rea
Nuclear Fusion 64 (12), 126005, 2024
42024
Corrigendum: hybrid deep learning architecture for general disruption prediction across tokamaks (2021 Nucl. Fusion 61 026007)
JX Zhu, C Rea, K Montes, RS Granetz, R Sweeney, RA Tinguely
Nuclear Fusion 61 (4), 049501, 2021
42021
Empirical probability and machine learning analysis of m, n= 2, 1 tearing mode onset parameter dependence in DIII-D H-mode scenarios
L Bardóczi, NJ Richner, J Zhu, C Rea, NC Logan
Physics of Plasmas 30 (9), 2023
32023
Data-driven study of major disruption prediction and plasma instabilities across multiple tokamaks
J Zhu
Massachusetts Institute of Technology, 2023
32023
Observation of a beam-driven low-frequency mode in Heliotron J
LG Zang, S Yamamoto, DA Spong, K Nagasaki, S Ohshima, S Kobayashi, ...
Nuclear Fusion 59 (5), 056001, 2019
32019
Hybrid deep learning architecture for general disruption prediction across tokamaks (vol 61, 026007, 2021)
JX Zhu, C Rea, K Montes, RS Granetz, R Sweeney, RA Tinguely
NUCLEAR FUSION 61 (4), 2021
12021
Development of a correlation ECE radiometer for electron temperature fluctuation measurements in Heliotron J
GM Weir, K Nagasaki, J Zhu, M Luo, H Okada, T Minami, S Kado, ...
EPJ Web of Conferences 203, 03013, 2019
12019
Root Cause of Disruptive NTMs in DIII-D ITER Baseline Scenario Plasma
L Bardoczi, N Richner, N Logan, J Zhu, C Rea, E Strait
APS Division of Plasma Physics Meeting Abstracts 2023, TI01. 001, 2023
2023
Overview of SPARC disruption prediction and avoidance research
C Rea, P Kaloyannis, Z Keith, A Maris, A Saperstein, L Spangher, ...
APS Division of Plasma Physics Meeting Abstracts 2023, JP11. 120, 2023
2023
Preparing for Disruptions in the SPARC Q> 1 Campaign
R Sweeney, D Battaglia, A Battey, S Benjamin, T Body, J Boguski, ...
APS Division of Plasma Physics Meeting Abstracts 2023, JP11. 119, 2023
2023
Do Fusion Plasma Time-Series Have a Persistent Memory that Machine Learning May Exploit?
L Spangher, J Zhu, C Rea, A Spangher, W Arnold, M Bonotto, F Cannarile, ...
APS Division of Plasma Physics Meeting Abstracts 2023, JP11. 121, 2023
2023
Interpretable Machine Learning Accelerating Fusion Research
C Rea, J Zhu, R Granetz, K Montes, R Tinguely, R Sweeney, N Howard, ...
APS Division of Plasma Physics Meeting Abstracts 2022, CT02. 001, 2022
2022
Disruption Research for SPARC
C Rea, R Sweeney, R Tinguely, R Granetz, D Garnier, B Stein-Lubrano, ...
APS Division of Plasma Physics Meeting Abstracts 2022, NO03. 007, 2022
2022
Empirical boundary detection of tearing mode onset at DIII-D
J Zhu, C Rea, R Granetz, E Marmar, R Sweeney, F Turco, K Erickson, ...
APS Division of Plasma Physics Meeting Abstracts 2022, GP11. 035, 2022
2022
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