Machine-learning assisted steady-state profile predictions using global optimization techniques

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Summary, etc.：: 乱流流束の分布勾配に対する敏感な依存性のために、硬い輸送モデルを用いた安定した分布予測は困難である。この困難を克服するため、大域的最適化手法を用いた新しい定常輸送コードGOTRESSが開発された。硬い輸送モデルを用いたシミュレーションで生じがちな数値的不安定なしに、滑らかな拡散係数や温度分布を得るこ...

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Material Type: 文書・図像類
Title: Machine-learning assisted steady-state profile predictions using global optimization techniques
Author/Editor: 本多, 充
成田, 絵美
Honda, Mitsuru
Narita, Emi
Author Heading: 本多, 充
成田, 絵美
Honda, Mitsuru
Narita, Emi
Publication Date: 2019-08-08
Publication Date (W3CDTF): 2019-08-08
Text Language Code: jpn
Target Audience: 一般
Note (General): 第25回NEXT（数値トカマク）研究会
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 国立研究開発法人量子科学技術研究開発機構 : 量子科学技術研究開発機構学術機関リポジトリ