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Neural-network accelerated coupled core-pedestal simulations with self-consistent transport of impurities and compatible with ITER IMAS

O. Meneghini, G. Snoep, B.C. Lyons, J. McClenaghan, C.S. Imai, B. Grierson, S.P. Smith, G.M. Staebler, P.B. Snyder, J. Candy2021年被引用 45Nuclear FusionIF 3出版社

An integrated modeling workflow capable of finding the steady-state plasma solution with self-consistent core transport, pedestal structure, current profile, and plasma equilibrium physics has been developed and tested against a DIII-D discharge. Key features of the achieved core-pedestal coupled workflow are its ability to account for the transport of impurities in the plasma self-consistently, as well as its use of machine learning accelerated models for the pedestal structure and for the turbulent transport physics. Notably, the coupled workflow is implemented within the One Modeling Framework for Integrated Tasks (OMFIT) framework, and makes use of the ITER integrated modeling and analysis suite data structure for exchanging data among the physics codes that are involved in the simulations. Such technical advance has been facilitated by the development of a new numerical library named ordered multidimensional arrays structure.

日本語訳

自己無撞着なコア輸送、ペデスタル構造、電流分布、およびプラズマ平衡物理を備えた定常状態プラズマ解を見つけることができる統合モデリングワークフローが開発され、DIII-D放電に対して検証された。達成されたコア-ペデスタル結合ワークフローの主な特徴は、プラズマ中の不純物輸送を自己無撞着に考慮できること、ならびにペデスタル構造および乱流輸送物理に対して機械学習加速モデルを使用することである。注目すべきことに、この結合ワークフローはOne Modeling Framework for Integrated Tasks(OMFIT)フレームワーク内で実装され、シミュレーションに関与する物理コード間でデータを交換するためにITER統合モデリング・解析スイートのデータ構造を利用している。このような技術的進歩は、ordered multidimensional arrays構造と名付けられた新しい数値ライブラリの開発によって促進された。

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iter高精度(タイトル一致)diii-d低精度(概要文一致)

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ITERImpurityPedestal
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