# Fourier-spectral element approximation of the two fluid ion-electron Braginskii system with application to tokamak edge plasma in divertor configuration

1 CASTOR - Control, Analysis and Simulations for TOkamak Research
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Due to the extreme conditions required to produce energy by nuclear fusion in tokamaks, simulating the plasma behavior is an important but challenging task. We focus on the edge part of the plasma, where fluid approaches are probably the best suited, and our approach relies on the Braginskii ion–electron model. Assuming that the electric field is electrostatic, this yields a set of 10 strongly coupled and non-linear conservation equations that exhibit multiscale and anisotropy features. The computational domain is a torus of complex geometrical section, that corresponds to the divertor configuration, i.e. with an “X-point” in the magnetic surfaces. To capture the complex physics that is involved, high order methods are used: The time-discretization is based on a Strang splitting, that combines implicit and explicit high order Runge–Kutta schemes, and the space discretization makes use of the spectral element method in the poloidal plane together with Fourier expansions in the toroidal direction. The paper thoroughly describes the algorithms that have been developed, provides some numerical validations of the key algorithms and exhibits the results of preliminary numerical experiments. In particular, we point out that the highest frequency of the system is intermediate between the ion and electron cyclotron frequencies.
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Journal articles
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Cited literature [44 references]

https://hal.univ-cotedazur.fr/hal-01328772
Contributor : Richard Pasquetti <>
Submitted on : Monday, October 17, 2016 - 2:13:29 PM
Last modification on : Wednesday, December 4, 2019 - 3:15:04 PM

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Sebastian Minjeaud, Richard Pasquetti. Fourier-spectral element approximation of the two fluid ion-electron Braginskii system with application to tokamak edge plasma in divertor configuration. Journal of Computational Physics, Elsevier, 2016, 321, pp.492-511. ⟨10.1016/j.jcp.2016.05.056⟩. ⟨hal-01328772⟩

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