Results 91 to 100 of about 4,253 (208)

Gyrokinetic simulations of the effects of magnetic islands on microturbulence in KSTAR

Nuclear Fusion
Gyrokinetic simulations are utilized to study effects of magnetic islands (MIs) on the ion temperature gradient (ITG) turbulence in the KSTAR tokamak with resonant magnetic perturbations. Simulations show that the transport is controlled by the nonlinear
Xishuo Wei, Javier H Nicolau, Gyungjin Choi, Zhihong Lin, Seong-Moo Yang, SangKyeun Kim, WooChang Lee, Chen Zhao, Tyler Cote, JongKyu Park, Dmitri Orlov   +10 more
doaj   +1 more source

Real-time data-driven disruption prediction and its mitigation of MA-plasma experiments in KSTAR with a lower carbon divertor

Nuclear Fusion
Real-time disruption prediction and its mitigation of mega-ampere (MA) plasma experiments have been performed in the 2022 KSTAR carbon lower divertor condition.
Jeongwon Lee, Sang-hee Hahn, Hyunsun Han, Jayhyun Kim, June-Woo Juhn, Jun-Gyo Bak, Jae-in Song, YongUn Nam   +7 more
doaj   +1 more source

Prompt loss of beam ions in KSTAR plasmas

AIP Advances, 2016
For a toroidal plasma facility to realize fusion energy, researching the transport of fast ions is important not only due to its close relation to the heating and current drive efficiencies but also to determine the heat load on the plasma-facing ...
Jun Young Kim, T. Rhee, Junghee Kim, S. W. Yoon, B. H. Park, M. Isobe, K. Ogawa, W. -H. Ko   +7 more
doaj   +1 more source

An overview of 3D field optimization for control of transport and edge instabilities on KSTAR

Nuclear Fusion
An international team from several laboratories and universities has made key advances over the last few years in the control of plasma transport and edge instabilities with applied 3D fields in the KSTAR tokamak to optimize long pulse operation ...
J.A. Snipes, J. Butt, C.S. Byun, T. Cote, K. Erickson, H.G. Frerichs, S.H. Hahn, Q. Hu, Y.M. Jeon, V. Khavin, M. Kim, S.K. Kim, M.W. Kim, W.H. Ko, E. Kolemen, N. Leuthold, Z. Lin, Y. Liu, N.C. Logan, P. Lunia, D. Orlov, G.Y. Park, J.K. Park, C. Paz-Soldan, A. Rothstein, G.W. Shin, R. Shousha, X. Sun, J. Van Blarcum, X. Wei, S.M. Yang, Y. Yu, C. Zhao, B. Zhu   +33 more
doaj   +1 more source

Ray Tracing Study on Top ECCD Launch in KSTAR

EPJ Web of Conferences, 2017
The current drive efficiency of electron cyclotron (EC) wave is typically low compared with other RF and neutral beam heating system in tokamak. It is known that EC current drive by outboard launch suffers from low current drive efficiency due to ...
Bae Young-soon, Namkung W., Cho M.H.
doaj   +1 more source

Analysis of synchrotron radiation emitted by runaway electrons in TOKAMAKS

East European Journal of Physics, 2013
The synchrotron radiation diagnostics allows a direct observation of the runaway electron beams and an analysis of their parameters. Strong oscillations of the instantaneous curvature radii of electron orbits were a characteristic feature of recent EAST ...
Igor Pankratov, Ivan Pavlenko, O. Pomazan   +2 more
doaj  

Series of powerful CW gyrotrons in the range 105 – 140 GHz

EPJ Web of Conferences, 2017
GYCOM in collaboration with Institute of Applied Physics (IAP) designed, fabricated and tested two different gyrotrons with similar to ITER parameters at 105 – 140 GHz frequency range.
Denisov Gregory, Kazansky Igor, Malygin Vladimir, Soluyanova Elena, Tai Evgeny, Chirkov Aleksey   +5 more
doaj   +1 more source

On FIRE mode in KSTAR

Nuclear Fusion
We report on the status of Fast Ion Regulated Enhancement (FIRE) mode experiments in the Korea Superconducting Tokamak Advanced Research. This regime is being developed for high-performance, steady-state operation which features a stationary ion internal
Yong-Su Na, S.J. Park, H. Han, Janghyeok Lee, C. Heo, S.C. Hong, C. Sung, D. Kim, J. Kang, Y.H. Lee, J. Chung, T.S. Hahm, B. Kim, J.G. Bak, R. Budny, M.S. Cha, G.J. Choi, M.J. Choi, J. Gwak, S.H. Hahn, J. Jang, K.C. Lee, J.H. Kim, S.K. Kim, W.C. Kim, J. Ko, W.H. Ko, C.Y. Lee, J.H. Lee, J.H. Lee, J.K. Lee, J.P. Lee, K.D. Lee, J.-K. Park, J.M. Park, Y.S. Park, J. Seo, S.M. Yang, S.W. Yoon, KSTAR Team   +39 more
doaj   +1 more source

Potential of Machine Learning for Predicting Sleep Disorders: A Comprehensive Analysis of Regression and Classification Models. [PDF]

Diagnostics (Basel), 2023
Alazaidah R, Samara G, Aljaidi M, Haj Qasem M, Alsarhan A, Alshammari M.   +5 more
europepmc   +1 more source

GS-DeepNet: mastering tokamak plasma equilibria with deep neural networks and the Grad-Shafranov equation. [PDF]

Sci Rep, 2023
Joung S, Ghim YC, Kim J, Kwak S, Kwon D, Sung C, Kim D, Kim HS, Bak JG, Yoon SW.   +9 more
europepmc   +1 more source