Moment approach to the bootstrap current in nonaxisymmetric toroidal plasmas using δf Monte Carlo methods

被引：6

作者：

Matsuyama, A. ^{[1
]}

Isaev, M. Yu. ^{[2
]}

Watanabe, K. Y. ^{[3
]}

Hanatani, K. ^{[4
]}

Suzuki, Y. ^{[3
]}

Nakajima, N. ^{[3
]}

Cooper, W. A. ^{[5
]}

Tran, T. M. ^{[5
]}

机构：

[1] Kyoto Univ, Grad Sch Energy Sci, Kyoto 6110011, Japan

[2] RRC Kurchatov Inst, Nucl Fus Inst, Moscow 123182, Russia

[3] Natl Inst Nat Sci, Natl Inst Fus Sci, Toki, Gifu 5095292, Japan

[4] Kyoto Univ, Inst Adv Energy, Kyoto 6110011, Japan

[5] Ecole Polytech Fed Lausanne, Ctr Rech Phys Plasmas, Assoc Euratom Suisse, CH-1015 Lausanne, Switzerland

来源：

PHYSICS OF PLASMAS | 2009年 / 16卷 / 05期

基金：

瑞士国家科学基金会;

关键词：

method of moments; Monte Carlo methods; plasma collision processes; plasma kinetic theory; plasma simulation; plasma toroidal confinement; plasma transport processes; stellarators; LARGE HELICAL DEVICE; NEOCLASSICAL TRANSPORT; COEFFICIENTS; SYSTEMS; COLLISIONALITY; CONFIGURATIONS; STELLARATORS; CONFINEMENT; IMPURITIES; SIMULATION;

D O I：

10.1063/1.3121223

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：

To evaluate the bootstrap current in nonaxisymmetric toroidal plasmas quantitatively, a delta f Monte Carlo method is incorporated into the moment approach. From the drift-kinetic equation with the pitch-angle scattering collision operator, the bootstrap current and neoclassical conductivity coefficients are calculated. The neoclassical viscosity is evaluated from these two monoenergetic transport coefficients. Numerical results obtained by the delta f Monte Carlo method for a model heliotron are in reasonable agreement with asymptotic formulae and with the results obtained by the variational principle.

引用

页数：9

共 50 条

[31] Statistical analysis of discrepant radioecological data using Monte Carlo Bootstrap Method
Casado da Silva, Arykerne Nascimento
Amaral, Romilton dos Santos
dos Santos Junior, Jose Araujo
Vieira, Jose Wilson
Cezar Menezes, Romulo Simoes
JOURNAL OF RADIOANALYTICAL AND NUCLEAR CHEMISTRY, 2015, 306 (03) : 571 - 577
[32] Some current issues in quasi-Monte Carlo methods
Niederreiter, H
JOURNAL OF COMPLEXITY, 2003, 19 (03) : 428 - 433
[33] Statistical analysis of discrepant radioecological data using Monte Carlo Bootstrap Method
Arykerne Nascimento Casado da Silva
Romilton dos Santos Amaral
José Araújo dos Santos Júnior
José Wilson Vieira
Rômulo Simões Cezar Menezes
Journal of Radioanalytical and Nuclear Chemistry, 2015, 306 : 571 - 577
[34] Pricing and hedging American options by Monte Carlo methods using a Malliavin calculus approach
Bally, Vlad
Caramellino, Lucia
Zanette, Antonino
MONTE CARLO METHODS AND APPLICATIONS, 2005, 11 (02): : 97 - 133
[35] An alternative approach to relapse analysis: Using Monte Carlo methods and proportional rates of response
Friedel, Jonathan E.
Galizio, Ann
Berry, Meredith S.
Sweeney, Mary M.
Odum, Amy L.
JOURNAL OF THE EXPERIMENTAL ANALYSIS OF BEHAVIOR, 2019, 111 (02) : 289 - 308
[36] An approach to determining the uncertainty in reactor test objects using deterministic and Monte Carlo methods
Keith, Robert E.
REACTOR DOSIMETRY: 12TH INTERNATIONAL SYMPOSIUM, 2008, 1490 : 373 - 385
[37] Monte Carlo simulation of Langmuir probe methods for plasmas having RF amplitude oscillations
Matsuoka, Akio, 1600, JJAP, Minato-ku, Japan (33):
[38] BAYESIAN COMPRESSIVE SENSING USING MONTE CARLO METHODS
Kyriakides, Ioannis
Pribic, Radmila
2013 PROCEEDINGS OF THE 21ST EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2013,
[39] Reconstruction of random media using Monte Carlo methods
Manwart, C
Hilfer, R
PHYSICAL REVIEW E, 1999, 59 (05): : 5596 - 5599
[40] Tomographic reconstruction using heuristic Monte Carlo methods
Barbuzza, R.
Venere, M.
Clausse, A.
JOURNAL OF HEURISTICS, 2007, 13 (03) : 227 - 242

← 1 2 3 4 5 →