3 papers
physics.plasm-ph2021
Proof of concept of a fast surrogate model of the VMEC code via neural networks in Wendelstein 7-X scenarios
Andrea Merlo, Daniel Böckenhoff, Jonathan Schilling +7
In magnetic confinement fusion research, the achievement of high plasma pressure is key to reaching the goal of net energy production. The magnetohydrodynamic (MHD) model is used t…
physics.data-an2020
Deep learning for Gaussian process tomography model selection using the ASDEX Upgrade SXR system
Francisco Matos, Jakob Svensson, Andrea Pavone +2
Gaussian process tomography (GPT) is a method used for obtaining real-time tomographic reconstructions of the plasma emissivity profile in a tokamak, given some model for the under…
physics.plasm-ph2020
Heat and particle flux detachment with stable plasma conditions in the Wendelstein 7-X stellarator fusion experiment
Marcin Jakubowski, Ralf König, Oliver Schmitz +30
Reduction of particle and heat fluxes to plasma facing components is critical to achieve stable conditions for both the plasma and the plasma material interface in magnetic confine…