High-order discretization of a gyrokinetic Vlasov model in edge plasma geometry

JOURNAL OF COMPUTATIONAL PHYSICS

卷:373

Article

Dorr, Milo R.¹  Colella, Phillip³  Dorf, Mikhail A.²  Ghosh, Debojyoti¹  Hittinger, Jeffrey A. F.¹  Schwartz, Peter O.³ 

[1] Lawrence Livermore Natl Lab, Ctr Appl Sci Comp, 7000 East Ave L-561, Livermore, CA 94550 USA

[2] Lawrence Livermore Natl Lab, Fus Energy Program, 7000 EastAve L-630, Livermore, CA 94550 USA

[3] Lawrence Berkeley Natl Lab, Appl Numer Algorithms Grp, One Cyclotron Rd Mail Stop 50A-1148, Berkeley, CA 94720 USA

关键词: Gyrokinetic;    Tokamak edge plasma;    High-order;    Mapped-multiblock;    Finite-volume;   

DOI  :  10.1016/j.jcp.2018.07.008

来源: Elsevier

【 摘 要 】

We describe a new spatial discretization of a continuum gyrokinetic Vlasov model in axisymmetric tokamak edge plasma geometries. The geometries are represented using a multiblock decomposition in which logically distinct blocks are smoothly mapped from rectangular computational domains and are aligned with magnetic flux surfaces to accommodate strong anisotropy induced by the magnetic field. We employ a fourth-order, finite-volume discretization in mapped coordinates to mitigate the computational expense associated with discretization on 4D phase space grids. Applied to a conservative formulation of the gyrokinetic system, a finite-volume approach expresses local conservation discretely in a natural manner involving the calculation of normal fluxes at cell faces. In the approach presented here, the normal fluxes are computed in terms of face-averaged velocity normals in such a way that (i) the divergence-free property of the gyrokinetic velocity is preserved discretely to machine precision, (ii) the configuration space normal velocities are independent of mapping metrics, and (iii) the configuration space normal velocities are computed from exact pointwise evaluation of magnetic field data except for one term. The algorithms described in this paper form the foundation of a continuum gyrokinetic edge code named COGENT, which is used here to perform a convergence study verifying the accuracy of the spatial discretization. (C) 2018 Elsevier Inc. All rights reserved.

【 授权许可】

Free