Robert Granetz

发表

Studies of the DIII-D disruption database using Machine Learning algorithms

Cristina Rea, Robert Granetz, Orso Meneghini, 2017 .

Scenario Development for SPARC

Ian H. Hutchinson, Charles Kessel, Dan Brunner, 2019 .

Advancing Fusion with Machine Learning Research Needs Workshop Report

Valerio Pascucci, Earl Lawrence, Egemen Kolemen, 2019, Journal of Fusion Energy.

Comparison of Recursive Neural Networks and Random Forests for disruption prediction on C-Mod

Jinxiang Zhu, Cristina Rea, Kevin Montes, 2019 .

Disruption prediction using a full convolutional neural network on EAST

Heng Zhang, Cristina Rea, Jinping Qian, 2020, Plasma Physics and Controlled Fusion.

Multi-machine Disruption Databases and Applications of Machine Learning for Fusion

Cristina Rea, Kevin Montes, Robert Granetz, 2018 .

Advancing Fusion with Machine Learning Research Needs Workshop Report

Valerio Pascucci, Earl Lawrence, Mark D. Boyer, 2020 .

Confinement mode identification of fusion plasmas utilizing machine learning methods

Cristina Rea, A. E. Hubbard, Jerry Hughes, 2018 .

20 years of research on the Alcator C-Mod tokamak

B. P. Duval, J. Stillerman, P. B. Snyder, 2014 .

Transport-driven scrape-off layer flows and the x-point dependence of the L-H power threshold in Alcator C-Mod

S. J. Wukitch, J. Irby, Jerry Hughes, 2005 .

H-Mode Power Threshold Database for ITER

Norio Suzuki, O. J. W. F. Kardaun, Tomonori Takizuka, 1996 .

Using mixed gases for massive gas injection disruption mitigation on Alcator C-Mod

Mohammad Bakhtiari, D. G. Whyte, M. L. Reinke, 2010 .

Magnetic separatrix experiments in JET

Richard D. Gill, P. Noll, M. Keilhacker, 1987 .

Establishment and Assessment of Plasma Disruption and Warning Databases from EAST

Xiao Bingjia, Robert Granetz, Wang Bo, 2016 .