Insights on divertor turbulence from first-principle modelling and comparison with experiments

ORAL

Abstract

The effect of turbulence in broadening the target heat flux profile and its precise contribution to the power exhaustion handling in tokamak plasmas are not fully understood. Previous studies have shown that fluctuations, fluxes, and scale lengths in the scrape-off layer are strongly influenced by field-aligned filaments (or blobs) [1]. Recently, the validation of the first full-size 3D edge turbulence simulations of a diverted TCV plasma revealed considerable discrepancies in the divertor and at the targets in comparison to the experiments [2]. In particular, the absence of divertor-localized blobs, small circular structures observed by Gas Puffing Imaging along the divertor leg for sufficiently high values of plasma current and which, according to simplified estimates, contribute significantly to target profile broadening [3]. In this contribution, we present progress on the understanding of turbulent transport around the X-point and in the divertor region using simulations carried out with GBS, a 3D flux-driven, global, two-fluid turbulence code including a kinetic equation for neutrals [4], and comparisons with experiments. By performing a plasma current scan with the simulations, we address the condition for the formation of divertor-localized blobs and quantify the contribution of divertor turbulence on the cross-field transport. These results are compared with high-resolution measurements across the divertor of similar plasmas in TCV provided by the X-point GPI system [3] and a reciprocating divertor probe array [5].

[1] D’Ippolito et al Phys. Plasmas 18 060501 (2011)

[2] D. S. Oliveira, T. Body et al Nucl. Fusion in press

[3] C. Wüthrich et al Nucl. Fusion submitted

[4] Giacomin J. Comput. Phys. 463 111294 (2022)

[5] H. Oliveira et al Rev. Sci. Instrum. 92 043547 (2021)

Presenters

  • Diego Sales de Oliveira

    • Ecole Polytechnique Federale de Lausanne
    • École Polytechnique Fédérale de Lausanne

Authors

  • Diego Sales de Oliveira

    • Ecole Polytechnique Federale de Lausanne
    • École Polytechnique Fédérale de Lausanne
  • Davide Galassi

    • Ecole Polytechnique Federale de Lausanne
  • Christian Theiler

    • Ecole Polytechnique Federale de Lausanne
    • École Polytechnique Fédérale de Lausanne
  • Nicola Offeddu

    • Ecole Polytechnique Federale de Lausanne
    • École Polytechnique Fédérale de Lausanne
  • Curdin Wuthrich

    • Ecole Polytechnique Federale de Lausanne
    • École Polytechnique Fédérale de Lausanne
  • Kyungtak Lim

    • Ecole Polytechnique Federale de Lausanne
  • Davide Mancini

    • Ecole Polytechnique Federale de Lausanne
  • Paolo Ricci

    • Ecole Polytechnique Federale de Lausanne
    • EPFL
  • Yinghan Wang

    • Ecole Polytechnique Federale de Lausanne
  • Claudia Colandrea

    • Ecole Polytechnique Federale de Lausanne
  • Sophie Gorno

    • Ecole Polytechnique Federale de Lausanne
    • Ecole Polytechnique Federal de Lausanne
  • Kenneth Lee

    • Ecole Polytechnique Federale de Lausanne
  • Holger Reimerdes

    • Ecole Polytechnique Federale de Lausanne
    • Ecole Polytechnique Federal de Lausanne
  • Tsui K Cedric

    • University of California
    • University of California, San Diego