Abstract
Tokamaks are fusion machines that are under development to produce baseload power. Baseload power is the power that is produced 24/7 and provides the base for powering the electric grid. The International Thermonuclear Experimental Reactor (ITER) is an international project that will produce net power from a Tokamak. Net power means the Tokamak produces more energy than it consumes. Consumption includes heating the plasma, controlling it, and powering all the auxiliary systems needed to maintain the plasma. It will allow researchers to study the physics of the Tokamak which will hopefully lead the way toward operational machines.
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References
M.M.M. Al-Husari, B. Hendel, I.M. Jaimoukha, E.M. Kasenally, D.J.N. Limebeer, and A.Portone. Vertical stabilisation of Tokamak Plasmas. In Proceedings of the 30th Conference on Decision and Control, December 1992.
Barbara Cannas, Gabriele Murgia, A Fanni, Piergiorgio Sonato, Augusto Montisci, and M.K. Zedda. Dynamic Neural Networks for Prediction of Disruptions in Tokamaks. CEUR Workshop Proceedings, 284, 01 2007.
Wroblewski D. and et al. Tokamak disruption alarm based on neural network model of high-beta limit. Nuclear Fusion, 37(725), 11 1997.
Julian Kates-Harbeck, Alexey Svyatkovskiy, and William Tang. Predicting disruptive instabilities in controlled fusion plasmas through deep learning. Nature, 568:526–531, April 2019.
Y. Liang and JET EFDA Contributors. Overview of Edge Localized Modes Control in Tokamak Plasma. Technical Report Preprint of Paper for Fusion Science and Technology, JET-EFDA, 2017.
G.A. Ratta, J..Vega, A. Murari, the EUROfusion MSTTeam, and JET Contributors. AUG-JET cross-tokamak disruption predictor. In 2nd IAEA TM, 2017.
Elizabeth Rosenthal. Artificial Intelligence Approach Points to Bright Future for Fusion Energy. Oak Ridge National Laboratory, 2019.
R.O. Sayer, Y.K.M. Peng, J.C. Wesley, S.C. Jardin, CA General Atomics, San Diego, and NJ Princeton Univ. ITER disruption modeling using TSC (Tokamak Simulation Code). Technical report, Oak Ridge National Laboratory, 11 1989.
Luigi. Scibile. Non-linear control of the plasma vertical position in a tokamak. PhD thesis, University of Oxford, 1997.
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Paluszek, M., Thomas, S., Ham, E. (2022). Tokamak Disruption Detection. In: Practical MATLAB Deep Learning. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-7912-0_6
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DOI: https://doi.org/10.1007/978-1-4842-7912-0_6
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