Open AccessSelf-consistent core-pedestal transport simulations with neural network accelerated models
Author(s) -
O. Meneghini,
S. P. Smith,
P.B. Snyder,
G. M. Staebler,
J. Candy,
E. A. Belli,
L. L. Lao,
Mark Kostuk,
T. C. Luce,
T. Luda,
J.M. Park,
F. M. Poli
Publication year - 2017
Publication title -
nuclear fusion
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.774
H-Index - 120
eISSN - 1741-4326
pISSN - 0029-5515
DOI - 10.1088/1741-4326/aa7776
Subject(s) - pedestal , computer science , coupling (piping) , core (optical fiber) , artificial neural network , statistical physics , speedup , physics , materials science , artificial intelligence , history , operating system , telecommunications , archaeology , metallurgy
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