Conveners
Pattern Recognition
- Geert Verdoolaege (Ghent University)
Pattern Recognition
- Geert Verdoolaege (UGent)
Chenguang Wan 1,3, *, Feda Almuhisen 2 , Philippe Moreau 2 , Remy Nouailletas 2 , Zhisong Qu 1 , Youngwoo Cho 1 , Robin Varennes 1 , Kyungtak Lim 1 , Kunpeng Li 1 , Zhengping Luo 3 , Qiping Yuan 3 , Xavier Garbet 1,2
1 School...
Understanding the scaling of the L-H transition power threshold $P_\mathrm{LH}$ is crucial for the operation of future tokamaks such as ITER and SPARC[1~3]. However, multicollinearity of the predictor variables in the scaling makes it difficult to disentangle the effect on the power threshold of the individual plasma variables. In this study, we analyze the scaling of $P_\mathrm{LH}$ in a...
Intrinsic impurities in a magnetically confined fusion (MCF) plasma dilute the reaction fuel in the hot plasma core and, through their radiation, are detrimental to global energy confinement. Thus, the radiative patterns of impurity elements in a fusion plasma must be understood across the full range of temperatures achieved in present day MCF experiments.
For this purpose, we present a...
Edge-localized modes (ELMs) are quasi-periodic edge instabilities in tokamaks, accompanied by expulsion of heat and particles from the plasma. Large ELMs can heighten the risk of damage to the plasma-facing components (PFCs). However, under certain conditions, ELMs can exhibit strongly stochastic behavior, showing a mix of relatively small and larger bursts. This complicates the predictability...
Traditional first-principle-based tokamak plasma magnetic response models, while pos-
sessing clear physical significance, often exhibit significant deviations when compared
with actual experimental data, limiting our deep understanding of plasma dynamics pro-
cesses. This study develops an autoregressive neural network model based on improved
WaveNet architecture that directly learns...
