113 citations · 183 across the 5 of their papers we have counts for
5 papers
Towards practical reinforcement learning for tokamak magnetic control
Brendan D. Tracey, Andrea Michi, Yuri Chervonyi +15
Reinforcement learning (RL) has shown promising results for real-time control systems, including the domain of plasma magnetic control. However, there are still significant drawbac…
Integrated real-time supervisory management for off-normal-event handling and feedback control of tokamak plasmas
T. Vu, F. Felici, C. Galperti +7
For long-pulse tokamaks, one of the main challenges in control strategy is to simultaneously reach multiple control objectives and to robustly handle in real-time (RT) unexpected e…
Classification of tokamak plasma confinement states with convolutional recurrent neural networks
F. Matos, V. Menkovski, F. Felici +2
During a tokamak discharge, the plasma can vary between different confinement regimes: Low (L), High (H) and, in some cases, a temporary (intermediate state), called Dithering (D).…
Fast modeling of turbulent transport in fusion plasmas using neural networks
Karel Lucas van de Plassche, Jonathan Citrin, Clarisse Bourdelle +7
We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 mill…
A mimetic spectral element solver for the Grad-Shafranov equation
Artur Palha, Barry Koren, Federico Felici
In this work we present a robust and accurate arbitrary order solver for the fixed-boundary plasma equilibria in toroidally axisymmetric geometries. To achieve this we apply the mi…