Real-time prediction of high-density EAST disruptions using random forest
文献类型：期刊论文
| 作者 | Hu, W. H.4; Rea, C.5; Yuan, Q. P.4; Erickson, K. G.1; Chen, D. L.4; Shen, B.4; Huang, Y.4 ; Xiao, J. Y.2; Chen, J. J.2; Duan, Y. M.4
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| 刊名 | NUCLEAR FUSION
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| 出版日期 | 2021-06-01 |
| 卷号 | 61 |
| ISSN号 | 0029-5515 |
| 关键词 | disruption prediction EAST real time mitigation |
| DOI | 10.1088/1741-4326/abf74d |
| 通讯作者 | Rea, C.(crea@mit.edu) |
| 英文摘要 | A real-time disruption predictor using random forest was developed for high-density disruptions and used in the plasma control system (PCS) of the EAST tokamak for the first time. The disruption predictor via random forest (DPRF) ran in piggyback mode and was actively exploited in dedicated experiments during the 2019-2020 experimental campaign to test its real-time predictive capabilities in oncoming high-density disruptions. During dedicated experiments, the mitigation system was triggered by a preset alarm provided by DPRF and neon gas was injected into the plasma to successfully mitigate disruption damage. DPRF's average computing time of similar to 250 mu s is also an extremely relevant result, considering that the algorithm provides not only the probability of an impending disruption, i.e. the disruptivity, but also the so-called feature contributions, i.e. explainability estimates to interpret in real time the drivers of the disruptivity. DPRF was trained with a dataset of disruptions in which the electron density reached at least 80% of the Greenwald density limit, using the zero-dimensional signal routinely available to the EAST PCS. Through offline analysis, an optimal warning threshold on the DPRF disruptivity signal was found, which allows for a successful alarm rate of 92% and a false alarm rate of 9.9%. By analyzing the false alarm causes, we find that a fraction (similar to 15%) of the misclassifications are due to sudden transitions of plasma confinement from H- to L-mode, which often occur during high-density discharges in EAST. By analyzing DPRF feature contributions, it emerges that the loop voltage signal is that main cause of such false alarms: plasma signals more apt to characterize the confinement back-transition should be included to avoid false alarms. |
| WOS关键词 | PLASMA CONTROL ; LIMITS |
| 资助项目 | National MCF Energy R&D Program of China[2018YFE0302100] ; National Natural Science Foundation of China[12005264] ; National Natural Science Foundation of China[12075285] ; National Natural Science Foundation of China[U1867222] ; National Natural Science Foundation of China[11875293] ; National Natural Science Foundation of China[11775266] ; US Department of Energy, Office of Science, Office of Fusion Energy Sciences[DE-FC0204ER54698] ; US Department of Energy, Office of Science, Office of Fusion Energy Sciences[DE-SC0014264] ; US Department of Energy, Office of Science, Office of Fusion Energy Sciences[DE-AC02-09CH11466] ; President Foundation of Hefei Institutes of Physical Science, Chinese Academy of Sciences[YZJJ2020QN11] |
| WOS研究方向 | Physics |
| 语种 | 英语 |
| 出版者 | IOP PUBLISHING LTD |
| WOS记录号 | WOS:000655363500001 |
| 资助机构 | National MCF Energy R&D Program of China ; National Natural Science Foundation of China ; US Department of Energy, Office of Science, Office of Fusion Energy Sciences ; President Foundation of Hefei Institutes of Physical Science, Chinese Academy of Sciences |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/123765]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Rea, C. |
| 作者单位 | 1.Princeton Plasma Phys Lab, Princeton, NJ 08543 USA 2.Univ Sci & Technol China, Sch Nucl Sci & Technol, Hefei, Peoples R China 3.Anhui Univ Sci & Technol, Sch Mech Engn, Huainan, Peoples R China 4.Chinese Acad Sci, Inst Plasma Phys, Hefei, Peoples R China 5.MIT, Plasma Sci & Fus Ctr, Cambridge, MA 02139 USA |
| 推荐引用方式 GB/T 7714 | Hu, W. H.,Rea, C.,Yuan, Q. P.,et al. Real-time prediction of high-density EAST disruptions using random forest[J]. NUCLEAR FUSION,2021,61. |
| APA | Hu, W. H..,Rea, C..,Yuan, Q. P..,Erickson, K. G..,Chen, D. L..,...&Li, J. G..(2021).Real-time prediction of high-density EAST disruptions using random forest.NUCLEAR FUSION,61. |
| MLA | Hu, W. H.,et al."Real-time prediction of high-density EAST disruptions using random forest".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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