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Experiment data-driven modeling of tokamak discharge in EAST

文献类型：期刊论文

作者Wan,Chenguang1,2; Yu,Zhi2; Wang,Feng2; Liu,Xiaojuan2; Li,Jiangang1,2
刊名Nuclear Fusion
出版日期2021-04-29
卷号61
关键词tokamak discharge modeling machine learning
ISSN号0029-5515
DOI10.1088/1741-4326/abf419
通讯作者Wan,Chenguang() ; Li,Jiangang()
英文摘要AbstractA neural network model of tokamak discharge is developed based on the experimental dataset of a superconducting long-pulse tokamak (EAST) campaign 2016–2018. The purpose is to reproduce the response of diagnostic signals to actuator signals without introducing additional physical models. In the present work, the discharge curves of electron density ne, stored energy Wmhd, and loop voltage Vloop were reproduced from a series of actuator signals. For ne and Wmhd, the average similarity between the modeling results and the experimental data achieve 89% and 97%, respectively. The promising results demonstrate that the data-driven methodology provides an alternative to the physical-driven methodology for tokamak discharge modeling. The method presented in the manuscript has the potential of being used for validating the tokamak’s experimental proposals, which could advance and optimize experimental planning and validation.
语种英语
WOS记录号IOP:0029-5515-61-6-ABF419
出版者IOP Publishing
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/121849]  
专题中国科学院合肥物质科学研究院
通讯作者Wan,Chenguang; Li,Jiangang
作者单位1.University of Science and Technology of China, Hefei, 230026, China
2.Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
推荐引用方式
GB/T 7714		 Wan,Chenguang,Yu,Zhi,Wang,Feng,et al. Experiment data-driven modeling of tokamak discharge in EAST[J]. Nuclear Fusion,2021,61.
APA Wan,Chenguang,Yu,Zhi,Wang,Feng,Liu,Xiaojuan,&Li,Jiangang.(2021).Experiment data-driven modeling of tokamak discharge in EAST.Nuclear Fusion,61.
MLA Wan,Chenguang,et al."Experiment data-driven modeling of tokamak discharge in EAST".Nuclear Fusion 61(2021).

入库方式： OAI收割

来源：合肥物质科学研究院

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