Now showing items 55-57 of 2054

    • Hybrid deep learning architecture for general disruption prediction across tokamaks 

      Zhu, Jinxiang; Rea, Cristina; Montes, Kevin J.; Granetz, R.S.; Sweeney, Ryan; e.a. (IOP, 2020-08)
      In this paper, we present a new deep learning disruption prediction algorithm based on important findings from explorative data analysis which effectively allows knowledge transfer from existing devices to new ones, thereby ...
    • On the very high energy confinement observed in super H-mode DIII-D experiments 

      Ding, S.; Garofalo, A.M.; Knolker, M.; Marinoni, Alessandro; McClenaghan, J.; e.a. (IOP, 2020-01)
      Analysis of recent super H-mode experiments on DIII-D shows that high rotation, not high pedestal, plays the essential role in achieving very high confinement H98y2 > 1.5. Very high confinement is reached early on in the ...
    • Neoclassical transport in strong gradient regions of large aspect ratio tokamaks 

      Trinczek, Silvia; Parra, Felix I.; Catto, Peter J.; Calvo, Iván; Landreman, Matt (Cambridge University Press, 2022-12)
      We present a new neoclassical transport model for large aspect ratio tokamaks where the gradient scale lengths are of the size of the poloidal gyroradius. Previous work on neoclassical transport across transport barriers ...