Conference Report
| العنوان: | Conference Report |
|---|---|
| المؤلفون: | S.M. Gonzalez de Vicente, D. Mazon, M. Xu, S. Pinches, M. Churchill, A. Dinklage, R. Fischer, A. Murari, P. Rodriguez-Fernandez, J. Stillerman, J. Vega, G. Verdoolaege |
| المصدر: | Nuclear Fusion |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Nuclear and High Energy Physics, Condensed Matter Physics |
| الوصف: | The objective of the Fourth Technical Meeting on Fusion Data Processing, Validation and Analysis was to provide a platform during which a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolating needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics and synthetic diagnostics data analysis (including image processing, regression analysis, inverse problems, deep learning, machine learning, big data and physics-based models for control) reported at the meeting. The progress in these areas highlight trends observed in current major fusion confinement devices. A special focus is dedicated on data analysis requirements for ITER and DEMO with a particular attention paid to artificial intelligence for automatization and improving reliability of control processes. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25f18f087188cf5418d2dde174b2a5d9 https://hdl.handle.net/21.11116/0000-000C-F242-821.11116/0000-000C-F240-A |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....25f18f087188cf5418d2dde174b2a5d9 |
| قاعدة البيانات: | OpenAIRE |
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