M Tobin, S A Sabbagh, V Zamkovska, J D Riquezes, J Butt, G Cunningham, L Kogan, J Measures, S Blackmore, C Ham, J Harrison, J W Berkery, S Gerhardt, J G Bak, J Lee, S W Yoon and the MAST Upgrade Team
{"title":"利用数据驱动优化对 DECAF 中的多装置托卡马克等离子体进行垂直不稳定性预测和可控性评估","authors":"M Tobin, S A Sabbagh, V Zamkovska, J D Riquezes, J Butt, G Cunningham, L Kogan, J Measures, S Blackmore, C Ham, J Harrison, J W Berkery, S Gerhardt, J G Bak, J Lee, S W Yoon and the MAST Upgrade Team","doi":"10.1088/1361-6587/ad7531","DOIUrl":null,"url":null,"abstract":"Reliable vertical position control will be an essential element of any future tokamak-based fusion power plant in order to reduce disruptions and maximize performance. We investigate methods to improve vertical controllability boundary determination in plasma operational space and demonstrate a data-driven approach based on direct pseudoinversion of operational space data that is rigorously quantitative, applicable in real-time plasma control systems, and physically intuitive to interpret. Applied to historical shot data from entire run campaigns on the MAST-U, KSTAR, and NSTX tokamaks, this approach, implemented in DECAF, improves vertical displacement event identification accuracy to 98.9%–100%. Further, we explore the application of a physics-based vertical stability metric as an early warning forecaster for vertical displacement events. The development of a linear surrogate model for the plasma current density profile, with a coefficient of determination of 0.992 on the training dataset, enables potential employment of this forecaster in real-time. The application of this approach on historical data from the MAST-U MU02 campaign yields a forecaster with 62.6% accuracy, indicating promise for this method when further refined and potentially coupled with other stability metrics.","PeriodicalId":20239,"journal":{"name":"Plasma Physics and Controlled Fusion","volume":"145 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vertical instability forecasting and controllability assessment of multi-device tokamak plasmas in DECAF with data-driven optimization\",\"authors\":\"M Tobin, S A Sabbagh, V Zamkovska, J D Riquezes, J Butt, G Cunningham, L Kogan, J Measures, S Blackmore, C Ham, J Harrison, J W Berkery, S Gerhardt, J G Bak, J Lee, S W Yoon and the MAST Upgrade Team\",\"doi\":\"10.1088/1361-6587/ad7531\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reliable vertical position control will be an essential element of any future tokamak-based fusion power plant in order to reduce disruptions and maximize performance. We investigate methods to improve vertical controllability boundary determination in plasma operational space and demonstrate a data-driven approach based on direct pseudoinversion of operational space data that is rigorously quantitative, applicable in real-time plasma control systems, and physically intuitive to interpret. Applied to historical shot data from entire run campaigns on the MAST-U, KSTAR, and NSTX tokamaks, this approach, implemented in DECAF, improves vertical displacement event identification accuracy to 98.9%–100%. Further, we explore the application of a physics-based vertical stability metric as an early warning forecaster for vertical displacement events. The development of a linear surrogate model for the plasma current density profile, with a coefficient of determination of 0.992 on the training dataset, enables potential employment of this forecaster in real-time. The application of this approach on historical data from the MAST-U MU02 campaign yields a forecaster with 62.6% accuracy, indicating promise for this method when further refined and potentially coupled with other stability metrics.\",\"PeriodicalId\":20239,\"journal\":{\"name\":\"Plasma Physics and Controlled Fusion\",\"volume\":\"145 1\",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Plasma Physics and Controlled Fusion\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-6587/ad7531\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHYSICS, FLUIDS & PLASMAS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plasma Physics and Controlled Fusion","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1088/1361-6587/ad7531","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, FLUIDS & PLASMAS","Score":null,"Total":0}
Vertical instability forecasting and controllability assessment of multi-device tokamak plasmas in DECAF with data-driven optimization
Reliable vertical position control will be an essential element of any future tokamak-based fusion power plant in order to reduce disruptions and maximize performance. We investigate methods to improve vertical controllability boundary determination in plasma operational space and demonstrate a data-driven approach based on direct pseudoinversion of operational space data that is rigorously quantitative, applicable in real-time plasma control systems, and physically intuitive to interpret. Applied to historical shot data from entire run campaigns on the MAST-U, KSTAR, and NSTX tokamaks, this approach, implemented in DECAF, improves vertical displacement event identification accuracy to 98.9%–100%. Further, we explore the application of a physics-based vertical stability metric as an early warning forecaster for vertical displacement events. The development of a linear surrogate model for the plasma current density profile, with a coefficient of determination of 0.992 on the training dataset, enables potential employment of this forecaster in real-time. The application of this approach on historical data from the MAST-U MU02 campaign yields a forecaster with 62.6% accuracy, indicating promise for this method when further refined and potentially coupled with other stability metrics.
期刊介绍:
Plasma Physics and Controlled Fusion covers all aspects of the physics of hot, highly ionised plasmas. This includes results of current experimental and theoretical research on all aspects of the physics of high-temperature plasmas and of controlled nuclear fusion, including the basic phenomena in highly-ionised gases in the laboratory, in the ionosphere and in space, in magnetic-confinement and inertial-confinement fusion as well as related diagnostic methods.
Papers with a technological emphasis, for example in such topics as plasma control, fusion technology and diagnostics, are welcomed when the plasma physics is an integral part of the paper or when the technology is unique to plasma applications or new to the field of plasma physics. Papers on dusty plasma physics are welcome when there is a clear relevance to fusion.