Data for "Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches"
- Authors:
-
- Princeton Plasma Physics Laboratory; Princeton Plasma Physics Laboratory
- Lawrence Berkeley National Laboratory
- Princeton Plasma Physics Laboratory
- San Francisco State University
- CEA IRFM
- Massachusetts Institute of Technology
- Publication Date:
- DOE Contract Number:
- AC02-09CH11466
- Research Org.:
- Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- Subject:
- ICRF; data-driven; machine learning; neural networks; plasma heating; surrogate modeling; tokamak
- OSTI Identifier:
- 2447761
- DOI:
- https://doi.org/10.34770/g2gt-4694
Citation Formats
Sánchez-Villar, Álvaro, Bai, Z., Bertelli, N., Bethel, E.W., Hillairet, J., Perciano, T., Shiraiwa, S., Wallace, G.M., and Wright, J.C. Data for "Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches". United States: N. p., 2023.
Web. doi:10.34770/g2gt-4694.
Sánchez-Villar, Álvaro, Bai, Z., Bertelli, N., Bethel, E.W., Hillairet, J., Perciano, T., Shiraiwa, S., Wallace, G.M., & Wright, J.C. Data for "Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches". United States. doi:https://doi.org/10.34770/g2gt-4694
Sánchez-Villar, Álvaro, Bai, Z., Bertelli, N., Bethel, E.W., Hillairet, J., Perciano, T., Shiraiwa, S., Wallace, G.M., and Wright, J.C. 2023.
"Data for "Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches"". United States. doi:https://doi.org/10.34770/g2gt-4694. https://www.osti.gov/servlets/purl/2447761. Pub date:Sun Dec 31 23:00:00 EST 2023
@article{osti_2447761,
title = {Data for "Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches"},
author = {Sánchez-Villar, Álvaro and Bai, Z. and Bertelli, N. and Bethel, E.W. and Hillairet, J. and Perciano, T. and Shiraiwa, S. and Wallace, G.M. and Wright, J.C.},
abstractNote = {},
doi = {10.34770/g2gt-4694},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Dec 31 23:00:00 EST 2023},
month = {Sun Dec 31 23:00:00 EST 2023}
}
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