Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations
@inproceedings{Merlo2022PhysicsregularizedNN,
title={Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations},
author={Andrea Merlo and Daniel Bockenhoff and Jonathan Schilling and Samuel Aaron Lazerson and Thomas Sunn Pedersen and The W7-X Team},
year={2022}
}The stellarator is a promising concept to produce energy from nuclear fusion by magnetically confining a high-pressure plasma. Magnetohydrodynamics (MHD) describes how plasma pressure, current density and magnetic field interact. In a stellarator, the confining field is three-dimensional, and the computational cost of solving the 3D MHD equations currently limits stellarator comprehension, exploration and optimization. Although data-driven approaches have been proposed to provide fast 3D MHD…
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References
SHOWING 1-10 OF 94 REFERENCES
Proof of concept of a fast surrogate model of the VMEC code via neural networks in Wendelstein 7-X scenarios
- Computer ScienceNuclear Fusion
- 2021
Artificial neural network models able to quickly compute the equilibrium magnetic field of Wendelstein 7-X are presented, and the feasibility of a fast NN drop-in surrogate model for VMEC is shown, which opens up new operational scenarios where target applications could make use of magnetic equilibria at unprecedented scales.
Fast recovery of vacuum magnetic configuration of the W7-X stellarator using function parametrization and artificial neural networks
- Physics
- 2004
W7-X, a five-period, fully optimized stellarator, currently under construction at IPP-Greifswald, Germany, is built with superconducting coils to show the steady state capability of stellarators.…
Solving Equilibria with a Neural Network
- Physics
- 1995
A general method to solve differential equations that was introduced recently, based on the use of MLP-1 type neural networks, is applied to the fast solution of ideal magnetohydrodynamic (MHD)…
Gradient-based optimization of 3D MHD equilibria
- PhysicsJournal of Plasma Physics
- 2021
Using recently developed adjoint methods for computing the shape derivatives of functions that depend on magnetohydrodynamic (MHD) equilibria (Antonsen et al., J. Plasma Phys., vol. 85, issue 2,…
Physics and Engineering Design for Wendelstein VII-X
- Physics
- 1990
AbstractThe future experiment Wendelstein VII-X (W VII-X) is being developed at the Max-Planck-Institut fur Plasmaphysik. A Helical Advanced Stellarator (Helias) configuration has been chosen because…
Verification of the ideal magnetohydrodynamic response at rational surfaces in the VMEC code
- Physics
- 2016
The VMEC nonlinear ideal MHD equilibrium code [S. P. Hirshman and J. C. Whitson, Phys. Fluids 26, 3553 (1983)] is compared against analytic linear ideal MHD theory in a screw-pinch-like…
Steepest‐descent moment method for three‐dimensional magnetohydrodynamic equilibria
- Physics
- 1983
An energy principle is used to obtain the solution of the magnetohydrodynamic (MHD) equilibrium equation J×B−∇p=0 for nested magnetic flux surfaces that are expressed in the inverse coordinate…
Full linearized Fokker–Planck collisions in neoclassical transport simulations
- Physics
- 2011
The complete linearized Fokker–Planck collision operator has been implemented in the drift-kinetic code NEO (Belli and Candy 2008 Plasma Phys. Control. Fusion 50 095010) for the calculation of…
Preconditioned descent algorithm for rapid calculations of magnetohydrodynamic equilibria
- Computer Science
- 1991
Neural network differential equation and plasma equilibrium solver.
- PhysicsPhysical review letters
- 1995
A new generally applicable method to solve differential equations, based on neural networks, is proposed, which is especially promising for the three-dimensional plasma equilibrium problem.