図版検索 AI要約 wiki 日本の研究装置ジャーナル ChatGPT About

© 2026 FUSIONPAPERS

About 法務情報

トップに戻る

A new class of indicators for the model selection of scaling laws in nuclear fusion

I. Lupelli, A. Murari, P. Gaudio, M. Gelfusa, J. Vega2013年Fusion Engineering and DesignIF 1.7 出版社

この論文にはまだAI要約がありません。

関連論文

Impact of scaling laws on tokamak reactor dimensioning

2020Nuclear Fusion

Improved scaling law for the prediction of deuterium retention in beryllium co-deposits

2022Nuclear Fusion

Scaling laws from theory-based modeling for different regimes in the DEMO fusion reactor

2019Nuclear Fusion

Modelling performed for predictions of fusion power in JET DTE2: overview and lessons learnt

2023Nuclear Fusion

A statistical methodology to derive the scaling law for the H-mode power threshold using a large multi-machine database

2012Nuclear Fusion

Transport simulations of TFTR: theoretically based transport models and current scaling

1994Nuclear Fusion

Neutron yield scaling law in laser-cluster fusion experiments

2023Nuclear Fusion

A statistical method for model extraction and model selection applied to the temperature scaling of the L–H transition

2014Plasma Physics and Controlled Fusion

Non-power law scaling for access to the H-mode in tokamaks via symbolic regression

2013Nuclear Fusion

Robust scaling in fusion science: case study for the L-H power threshold

2015Nuclear Fusion