Plasma and Fusion Research

Volume 16, 2402010 (2021)

Regular Articles

Data-Driven Approach on the Mechanism of Radiative Collapse in the Large Helical Device
Tatsuya YOKOYAMA1,2), Hiroshi YAMADA1), Suguru MASUZAKI3,4,5), Junichi MIYAZAWA3,5), Kiyofumi MUKAI3,5), Byron J. PETERSON3,5), Naoki TAMURA3,5), Ryuichi SAKAMOTO3,5), Gen MOTOJIMA3,5), Katsumi IDA3), Motoshi GOTO3,5), Tetsutaro OISHI3,5), Gakushi KAWAMURA3,5), Masahiro KOBAYASHI3,5) and LHD Experiment Group3)
1)
Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8561, Japan
2)
Research Fellow of Japan Society for the Promotion of Science, Tokyo 102-0083, Japan
3)
National Institute for Fusion Science, National Institutes of Natural Sciences, Gifu 509-5292, Japan
4)
Research Institute for Applied Mechanics, Kyushu University, Fukuoka 816-8580, Japan
5)
The Graduate University for Advanced Studies, SOKENDAI, Gifu 509-5292, Japan
(Received 10 November 2020 / Accepted 17 December 2020 / Published 26 February 2021)

Abstract

A radiative collapse predictor has been developed using a machine-learning model based on high-density plasma experiments in the Large Helical Device (LHD). Concurrently, the physical background of radiative collapse was discussed based on the distinct features extracted by a sparse modeling, which is one of the frameworks of data-driven science. Electron density, CIV and OV line emissions, and electron temperature at the plasma edge have been extracted as the key parameters of radiative collapse. Those parameters are relevant to the physical knowledge that the major cause of radiative collapse is the enhancement of radiative loss by light impurities in the plasma-edge region. Using these four parameters, the likelihood of occurrence of radiative collapse has been estimated. The behavior of plasma at the edge—in particular, the carbon impurities outside the last closed flux surface—has been evaluated using EMC3-EIRENE code for the phase with increasing likelihood, that is, the plasma is getting close to the collapse. It is shown that the radiation caused by the C3+ ion, which corresponds to the CIV emission, is enhanced in the region where electron temperature is around 10 eV.

Keywords

Large Helical Device (LHD), radiative collapse, density limit, impurity, stellarator-heliotron plasma, sparse modeling, data-driven science, EMC3-EIRENE

DOI: 10.1585/pfr.16.2402010

Full Text

PDF format (1.9Mbytes) PDF Download

References

  • [1] S. Sudo et al., Nucl. Fusion 30(1), 11 (1990).
  • [2] K. Itoh, S.-I. Itoh and L. Giannone, J. Phys. Soc. Jpn. 70(11), 3274 (2001).
  • [3] B.J. Peterson et al., Phys. Plasmas 8(9), 3861 (2001).
  • [4] A. Murari et al., Nucl. Fusion 59(8), 086037 (2019).
  • [5] C. Rea et al., Nucl. Fusion 59(9), 096016 (2019).
  • [6] A. Pau et al., IEEE Trans. Plasma Sci. 46(7), 2691 (2018).
  • [7] J. Kates-Harbeck, A. Svyatkovskiy and W. Tang, Nature 568(7753), 526 (2019).
  • [8] T. Yokoyama et al., Fusion Eng. Des. 140, 67 (2019).
  • [9] C. Rea et al., Fusion Sci. Technol. 76(8), 912 (2020).
  • [10] C. Cortes and V. Vapnik, Machine Learning 20(3), 273 (1995).
  • [11] Y. Igarashi et al., J. Phys. Conf. Series 699(1), 012001 (2016).
  • [12] Y. Feng et al., Contrib. Plasma Phys. 44(1-3), 57 (2004).
  • [13] D. Reiter, M. Baelmans and P. Börner, Fusion Sci. Technol. 47(2), 172 (2005).
  • [14] G. Kawamura et al., Plasma Phys. Control. Fusion 60(8), 084005 (2018).
  • [15] B.J. Peterson et al., Plasma Fusion Res. 1, 045 (2006).
  • [16] Y. Igarashi et al., J. Phys. Conf. Series 1036, 012001 (2018).
  • [17] C. Van Rijsbergen, Information Retrieval (Butterworths, London, 1979).
  • [18] D. Post et al., Atomic Data Nucl. Data Tables 20(5), 397 (1977).
  • [19] K. Ida and S. Hidekuma, Rev. Sci. Instrum. 60(5), 867 (1989).