Application of the Ensemble Kalman Smoother to Turbulent Transport Analysis in LHD Plasma

被引：2

作者：

Morishita, Yuya ^{[1
]}

Murakami, Sadayoshi ^{[1
]}

Yokoyama, Masayuki ^{[2
,4
,5
]}

Ueno, Genta ^{[3
,4
,5
,6
]}

机构：

[1] Kyoto Univ, Dept Nucl Engn, Kyoto 6158540, Japan

[2] Natl Inst Fus Sci, Toki, Gifu 5095292, Japan

[3] Inst Stat Math, Tokyo 1908562, Japan

[4] Grad Univ Adv Studies, SOKENDAI, Toki, Gifu 5095292, Japan

[5] Grad Univ Adv Studies, SOKENDAI, Tokyo 1908562, Japan

[6] Joint Support Ctr Data Sci Res, Tokyo 1900014, Japan

来源：

PLASMA AND FUSION RESEARCH | 2021年 / 16卷

关键词：

data assimilation; ASTI; ensemble Kalman smoother; TASK3D; LHD;

D O I：

10.1585/pfr.16.2403016

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：

The ensemble Kalman smoother (EnKS) is introduced to the data assimilation system, ASTI, based on the integrated transport simulation code, TASK3D. We use the EnKS to estimate state variables composed of electron and ion temperature, density, and numerical factors of turbulent transport models and neutral beam injection (NBI) heat deposition. The time series data of plasma temperature and density profiles are assimilated into TASK3D. The estimation performance of the EnKS is investigated, and the EnKS is applied to an NBI plasma in the Large Helical Device (LHD) (shot:114053) to estimate the factors of the turbulent heat transport model. The obtained factors can reproduce the experimental temperature data with high accuracy. These results indicate the effectiveness and validity of the EnKS approach for accurate estimation of fusion plasma parameters. (C) 2021 The Japan Society of Plasma Science and Nuclear Fusion Research

引用

页码：2403016 / 1

页数：8

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[1] Application of the Ensemble Kalman Smoother to Turbulent Transport Analysis in LHD Plasma
Department of Nuclear Engineering, Kyoto University, Kyoto
615-8540, Japan
不详
509-5292, Japan
不详
190-8562, Japan
不详
Tokyo
509-5292, 190-8562, Japan
不详
190-0014, Japan
Plasma Fusion Res., 1600, (2403016-1-2403016-8):
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