2023 Fiscal Year Final Research Report
Thermal transport modelling of fusion plasmas based on large-scale transport analyses database
| Project/Area Number |
19K03797
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 14020:Nuclear fusion-related
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| Research Institution | National Institute for Fusion Science |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
山口 裕之 核融合科学研究所, 研究部, 准教授 (90797101)
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| Project Period (FY) |
2019-04-01 – 2024-03-31
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| Keywords | 核融合プラズマ / 熱輸送 / 大規模データベース / 統計解析 / 情報量規準 / 重要変数 / 統計数理核融合学 |
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| Outline of Final Research Achievements |
Regarding the problem of heat transport in fusion plasmas, we have created a new research trend based on a data-driven approach that makes full use of large-scale databases, which is different from elemental integrated research in plasma physics. Research using two approaches: the database accumulated through the construction and operation of an integrated transport analysis suite for the fusion plasma experiment (LHD), and the gap between models which (1) obtained from physics insights and (2) obtained from data assimilation, have been conducted. In both cases, we were able to obtain the interesting finding that when statistically important variables are extracted, variables that are recognized to be physically important are selected. Based on these achievements, we have applied such data-driven approach to other research topics (eg., scenario development for the record-breaking experiments) and then proposed new interdisciplinary research, "statistical-mathematical fusion research".
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| Free Research Field |
プラズマ物理・核融合科学
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| Academic Significance and Societal Importance of the Research Achievements |
要素統合的な研究と相補的なデータ駆動的アプローチを、高度に複雑な核融合プラズマの課題に適用し、データ駆動的アプローチの有用性とともに、その手法によって、リアルタイムでの予測や判断が必要とされる状況への適応性を各段に高め得ることを示すことができた。さらに、統計的に重要な変数であるとして選び出される変数が、物理的にも重要であることが認識されているものであるという知見も得ることができた。核融合プラズマ研究の新動向の端緒となるものであるが、他の研究分野にも同様の考え方が展開できる。
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