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Compressing the time series of five dimensional distribution function data from gyrokinetic simulation using principal component analysis
https://repo.qst.go.jp/records/81760
https://repo.qst.go.jp/records/81760aad7a97d-9287-4a09-83a2-af8dc2ef6e33
| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2021-02-02 | |||||
| タイトル | ||||||
| タイトル | Compressing the time series of five dimensional distribution function data from gyrokinetic simulation using principal component analysis | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| アクセス権 | ||||||
| アクセス権 | metadata only access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
| 著者 |
Asahi, Yuuichi
× Asahi, Yuuichi× Fujii, Keisuke× Manuel Heim, Dennis× Maeyama, Shinya× Garbet, Xavier× Grandgirard, Virginie× Sarazin, Yanick× Guilhem, Dif-Pradalier× Idomura, Yasuhiro× Yagi, Masatoshi× Yuuichi, Asahi× Yasuhiro, Idomura× Masatoshi, Yagi |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Phase space structures are extracted from the time series of five dimensional distribution function data computed by the flux-driven full-f gyrokinetic code GT5D. Principal component analysis (PCA) is applied to reduce the dimensionality and the size of the data. Phase space bases in ðu; vk;wÞ and the corresponding spatial coefficients (poloidal cross section) are constructed by PCA, where u; vk, and w, respectively, mean the toroidal angle, the parallel velocity, and the perpendicular velocity. It is shown that 83% of the variance of the original five dimensional distribution function can be expressed with 64 principal components, i.e., the compression of the degrees of freedom from 1:3 1012 to 1:4 109. One of the important findings—resulting from the detailed analysis of the contribution of each principal component to the energy flux—deals with avalanche events, which are found to be mostly driven by coherent structures in the phase space, indicating the key role of resonant particles. Another advantage of the proposed analysis is the decoupling of 6D (1D time and 5D phase space) data into the combinations of 3D data which are visible to the human eye. |
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| 書誌情報 |
Physics of Plasmas 巻 28, p. 012304, 発行日 2021-01 |
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| 出版者 | ||||||
| 出版者 | AIP Publishing | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 1070-664X | |||||
| DOI | ||||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.1063/5.0023166 | |||||
| 関連サイト | ||||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | https://doi.org/10.1063/5.0023166 | |||||
