This paper presents the subtleties of obtaining robust experimental scaling laws for the core resonant error field threshold that leads to field penetration, locked modes, and disruptions. Recent progress in attempts to project this threshold to new machines has focused on advances in the metric used to quantify the dangerous error fields, incorporating the ideal MHD plasma response in a metric referred to as the 'dominant mode overlap'. However, the scaling of this or any quantity with experimental parameters known to be important for the complicated tearing layer physics requires regressions performed for databases that, for historical reasons, unevenly sample the available parametric space. This paper presents the distribution of the existing international n = 1 database and details biases in the available sampling and details the sensitivity of ITER projections to simple least-squares regressions. Downsampling and a simple kernel density estimation weighted regression are used here to demonstrate the difference in projections that acknowledging the machine sampling bias can make. This results in more robust projection to parameters far from the 'usual' devices built thus far. Two multi-device and multi-parameter scalings of the EF threshold in Ohmic and powered plasmas are presented, projecting the threshold to ITER and investigating the impact of sampling biases.

Robustness of the tokamak error field correction tolerance scaling

Piovesan P;
2020

Abstract

This paper presents the subtleties of obtaining robust experimental scaling laws for the core resonant error field threshold that leads to field penetration, locked modes, and disruptions. Recent progress in attempts to project this threshold to new machines has focused on advances in the metric used to quantify the dangerous error fields, incorporating the ideal MHD plasma response in a metric referred to as the 'dominant mode overlap'. However, the scaling of this or any quantity with experimental parameters known to be important for the complicated tearing layer physics requires regressions performed for databases that, for historical reasons, unevenly sample the available parametric space. This paper presents the distribution of the existing international n = 1 database and details biases in the available sampling and details the sensitivity of ITER projections to simple least-squares regressions. Downsampling and a simple kernel density estimation weighted regression are used here to demonstrate the difference in projections that acknowledging the machine sampling bias can make. This results in more robust projection to parameters far from the 'usual' devices built thus far. Two multi-device and multi-parameter scalings of the EF threshold in Ohmic and powered plasmas are presented, projecting the threshold to ITER and investigating the impact of sampling biases.
2020
Istituto per la Scienza e Tecnologia dei Plasmi - ISTP
Inglese
62
8
084001-1
084001-8
8
https://iopscience.iop.org/article/10.1088/1361-6587/ab9a12/meta
Sì, ma tipo non specificato
error fields
ITER
tokamak
Article Number: 084001, Print-ISSN: 0741-3335, http://www.scopus.com/inward/record.url?eid=2-s2.0-85088899814&partnerID=q2rCbXpz This work was supported by the U.S. Department of Energy Office of Science Office of Fusion Energy Sciences using the DIII-D National Fusion Facility and Alcator C-Mod, both DOE Office of Science user facilities,under Awards DE-FC02-04ER54698, DE- AC02-09CH11466and DE-FC02-99ER54512. The work was also supported by the National Key R&D Program of China under Grant No. 2017YFE0301100, the Czech Science Founda-tion (GA CR) under the grant number 19-15229S, and by MEYS of CR projects number 8D15001 and LM2015045. The work has been carried out within the framework of the project COMPASS-U: Tokamak for cutting-edge fusion research (No. CZ.02.1.01/0.0/0.0/16_019/0000768) and co-funded from European structural and investment funds. This work has been carried out within the framework of thE EUROfusion Consortium and has received funding from the Euratom research and training program 2014-2018 and 2019-2020 under grant agreement No 633053.
14
info:eu-repo/semantics/article
262
Logan, Nc; Park, Jk; Hu, Q; Pazsoldan, C; Markovic, T; Wang, Hh; In, Y; Piron, L; Piovesan, P; Myers, Ce; Maraschek, M; Wolfe, Sm; Strait, Ej; Munaret...espandi
01 Contributo su Rivista::01.01 Articolo in rivista
none
   Implementation of activities described in the Roadmap to Fusion during Horizon 2020 through a Joint programme of the members of the EUROfusion consortium
   EUROfusion
   H2020
   633053
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/384827
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