Extensions of the 3-dimensional plasma transport code E3D

被引:6
作者
Runov, A [1 ]
Kasilov, S
Schneider, R
Reiter, D
机构
[1] EURATOM, Max Planck Inst Plasmaphys, D-17491 Greifswald, Germany
[2] Kharkov Phys & Technol Inst, Ctr Nat Sci, Inst Plasma Phys, UA-61108 Kharkov, Ukraine
[3] EURATOM, Inst Plasmaphys, KFA Julich GmbH, Forschungszentrum, D-52425 Julich, Germany
关键词
ergodic divertor; island divertor; stellarator; edge modelling;
D O I
10.1002/ctpp.200410002
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
One important aspect of modern fusion research is plasma edge physics. Fluid transport codes extending beyond the standard 2-D code packages like B2-Eirene or UEDGE are under development. A 3-dimensional plasma fluid code, E3D, based upon the Multiple Coordinate System Approach and a Monte Carlo integration procedure has been developed for general magnetic configurations including ergodic regions. These local magnetic coordinates lead to a full metric tensor which accurately accounts for all transport terms in the equations. Here, we discuss new computational aspects of the realization of the algorithm. The main limitation to the Monte Carlo code efficiency comes from the restriction on the parallel jump of advancing test particles which must be small compared to the gradient length of the diffusion coefficient. In our problems, the parallel diffusion coefficient depends on both plasma and magnetic field parameters. Usually, the second dependence is much more critical. In order to allow long parallel jumps, this dependence can be eliminated in two steps: first, the longitudinal coordinate x:3 of local magnetic coordinates is modified in such a way that in the new coordinate system the metric determinant and contra-variant components of the magnetic field scale along the magnetic field with powers of the magnetic field module (like in Boozer flux coordinates). Second, specific weights of the test particles are introduced. As a result of increased parallel jump length, the efficiency of the code is about two orders of magnitude better.
引用
收藏
页码:18 / 24
页数:7
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