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Integrated transport simulations with a neural-network transport model and development of turbulence saturation rules
https://repo.qst.go.jp/records/81911
https://repo.qst.go.jp/records/81911ef260d76-abe8-47d9-b7fd-937677b1ffb0
Item type | 会議発表論文 / Conference Paper(1) | |||||
---|---|---|---|---|---|---|
公開日 | 2021-02-19 | |||||
タイトル | ||||||
タイトル | Integrated transport simulations with a neural-network transport model and development of turbulence saturation rules | |||||
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_5794 | |||||
資源タイプ | conference paper | |||||
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 |
Emi, Narita
× Emi, Narita× Mitsuru, Honda× Motoki, Nakata× Maiko, Yoshida× Nobuhiko, Hayashi× Emi, Narita× Mitsuru, Honda× Maiko, Yoshida× Nobuhiko, Hayashi |
|||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | 準線形乱流輸送モデルDeKANISはニューラルネットワーク(NN)を用いることで、ジャイロ運動論コードが予測する拡散・ピンチ過程の輸送量への寄与を高速に再現できる。NNの学習に用いるデータの拡張などの改良によって、統合コードにおける輸送シミュレーションが可能になった。また、乱流揺動の飽和レベルは半経験的な手法で評価していたが、混合長理論に基づく手法を導入し、汎用性が以前よりも向上する可能性を示した。 | |||||
書誌情報 |
第18回核燃焼プラズマ統合コード研究会 発行日 2021-02 |