26 citations · 69 across the 7 of their papers we have counts for
7 papers
MAS: A versatile Landau-fluid eigenvalue code for plasma stability analysis in general geometry
Jian Bao, Wenlu Zhang, Ding Li +8
We have developed a new global eigenvalue code, Multiscale Analysis for plasma Stabilities (MAS), for studying plasma problems with wave toroidal mode number n and frequency omega…
Reconstruction of tokamak plasma safety factor profile using deep learning
Xishuo Wei, Ge Dong, Shuying Sun +3
In tokamak operations, accurate equilibrium reconstruction is essential for reliable real-time control and realistic post-shot instability analysis. The safety factor (q) profile d…
Implementation of AI/Deep Learning Disruption Predictor into a Plasma Control System
William Tang, Ge Dong, Jayson Barr +17
This paper reports on advances to the state-of-the-art deep-learning disruption prediction models based on the Fusion Recurrent Neural Network (FRNN) originally introduced a 2019 N…
Verification and validation of gyrokinetic and kinetic-MHD simulations for internal kink instability in DIII-D tokamak
G. Brochard, J. Bao, C. Liu +14
Verification and validation of the internal kink instability in tokamak have been performed for both gyrokinetic (GTC) and kinetic-MHD codes (GAM-solver, M3D-C1-K, NOVA, XTOR-K). U…
Fully Convolutional Spatio-Temporal Models for Representation Learning in Plasma Science
Ge Dong, Kyle Gerard Felker, Alexey Svyatkovskiy +2
We have trained a fully convolutional spatio-temporal model for fast and accurate representation learning in the challenging exemplar application area of fusion energy plasma scien…
Deep Residual Network for Sound Source Localization in the Time Domain
Dmitry Suvorov, Ge Dong, Roman Zhukov
This study presents a system for sound source localization in time domain using a deep residual neural network. Data from the linear 8 channel microphone array with 3 cm spacing is…