DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy ME Fenstermacher, J Abbate, S Abe, T Abrams, M Adams, B Adamson, ... Nuclear Fusion 62 (4), 042024, 2022 | 21 | 2022 |
Accelerated version of NUBEAM capabilities in DIII-D using neural networks SM Morosohk, MD Boyer, E Schuster Fusion Engineering and Design 163, 112125, 2021 | 15 | 2021 |
Neural network model of the multi-mode anomalous transport module for accelerated transport simulations SM Morosohk, A Pajares, T Rafiq, E Schuster Nuclear Fusion 61 (10), 106040, 2021 | 11 | 2021 |
Validating the Multi-Mode Model’s Ability to Reproduce Diverse Tokamak Scenarios T Rafiq, Z Wang, S Morosohk, E Schuster, J Weiland, W Choi, HT Kim Plasma 6 (3), 435-458, 2023 | 3 | 2023 |
Neural network model of neutral beam injection in the EAST tokamak to enable fast transport simulations Z Wang, S Morosohk, T Rafiq, E Schuster, MD Boyer, W Choi Fusion Engineering and Design 191, 113514, 2023 | 3 | 2023 |
Real‐time estimation of the electron temperature profile in DIII‐D by leveraging neural‐network surrogate models S Morosohk, E Schuster Contributions to Plasma Physics 63 (5-6), e202200153, 2023 | 3 | 2023 |
Control-oriented current-profile response modeling using neural network accelerated versions of TGLF and NUBEAM for DIII-D S Morosohk, T Rafiq, E Schuster, O Meneghini, MD Boyer APS Division of Plasma Physics Meeting Abstracts 2020, GP19. 029, 2020 | 2 | 2020 |
Machine learning-enhanced model-based scenario optimization for DIII-D S Morosohk, B Leard, T Rafiq, E Schuster Nuclear Fusion 64 (5), 056018, 2024 | 1 | 2024 |
Enhanced Plasma Profile Estimation and Control in Tokamaks via Machine Learning S Morosohk Lehigh University, 2024 | 1 | 2024 |
Estimation of the electron temperature profile in tokamaks using analytical and neural network models S Morosohk, A Pajares, E Schuster 2022 American Control Conference (ACC), 278-283, 2022 | 1 | 2022 |
Neural-network version of nubeam for real-time control and scenario optimization in DIII-D S Morosohk, D Boyer, E Schuster APS Division of Plasma Physics Meeting Abstracts 2018, BP11. 101, 2018 | 1 | 2018 |
Fast Neural-Network Surrogate Model of the Updated Multi-Mode Anomalous Transport Module for NSTX-U B Leard, Z Wang, S Morosohk, T Rafiq, E Schuster IEEE Transactions on Plasma Science, 2024 | | 2024 |
Current Profile Control in EAST via Reinforcement-Learning-based Model Predictive Control Z Wang, ST Paruchuri, S Morosohk, E Schuster APS Division of Plasma Physics Meeting Abstracts 2023, UP11. 054, 2023 | | 2023 |
Integration of MMMNet for NSTX-U into COTSIM to Enable Fast and Accurate Predictions for Scenario Planning and Control Applications B Leard, T Rafiq, S Morosohk, Z Wang, E Schuster APS Division of Plasma Physics Meeting Abstracts 2023, YP11. 064, 2023 | | 2023 |
Simultaneous Regulation of the Electron Temperature and Safety Factor Profiles for DIII-D using Optimal Control Methods S Morosohk, Z Wang, ST Paruchuri, T Rafiq, E Schuster APS Division of Plasma Physics Meeting Abstracts 2023, PP11. 011, 2023 | | 2023 |
Fusion-Plasma Response Modeling Through Neural Network Machine Learning S Kothari, S Morosohk, E Schuster Journal of Computing Sciences in Colleges 38 (3), 200-200, 2022 | | 2022 |
Robust Control of the Electron Temperature Profile in DIII-D S Morosohk, ST Paruchuri, Z Wang, T Rafiq, E Schuster APS Division of Plasma Physics Meeting Abstracts 2022, UP11. 061, 2022 | | 2022 |
Simultaneous Electron Temperature and Safety Factor Profile Control for DIII-D S Morosohk, Z Wang, A Pajares, ST Paruchuri, T Rafiq, E Schuster APS Division of Plasma Physics Meeting Abstracts 2021, CP11. 102, 2021 | | 2021 |
Model-based control development for KSTAR enabled by TRANSP M Boyer, X Yuan, F Poli, HS Kim, SH Hahn, E Schuster, S Morosohk, ... APS Division of Plasma Physics Meeting Abstracts 2019, CO6. 006, 2019 | | 2019 |
A Neural Network Version of Multi-Mode Model for Control-oriented Fast Simulations in DIII-D S Morosohk, E Schuster, T Rafiq APS Division of Plasma Physics Meeting Abstracts 2019, TP10. 137, 2019 | | 2019 |