First Achievement of Stationary Doublet Plasmas in the TCV Tokamak

ORAL  · Invited

Abstract

Stationary, long-lived doublet plasmas lasting several current redistribution times have been obtained for the first time ever. Doublets are tokamak equilibria with two distinct current maxima creating two 'lobes' delimited by a figure-8 separatrix and surrounded by a 'mantle' region of closed field lines. Doublets require simultaneous feedback control of two unstable n=0 modes and have proven challenging to stabilize in past efforts in a series of dedicated 'Doublet' devices (1969-1983) as well as in previous experiments on TCV. The recent breakthrough was enabled by the development of a multi-domain capable free-boundary Grad-Shafranov equilibrium evolution solver coupled with a toroidal current diffusion equation, which permitted extensive pre-shot closed-loop control simulations. Accurate control of the magnetic configuration is achieved by an advanced multivariable feedback controller acting directly on poloidal field coil voltages based on estimated last closed flux surface position errors at a set of control points. Doublets lasting up to 2s, or approximately 10 current redistribution times, are now routinely obtained. The plasmas have an elongation of kappa=3.1 using up the entire volume of the TCV vessel and exceeding TCV's record elongation of conventional, single-axis plasmas, without using in-vessel stabilizing coils. First diagnostic measurements and observations of these fully stationary doublet configurations will be presented, as well as first exploration and phenomenology of plasma current and density limits in heated and non-heated doublet scenarios. This novel development offers new and exciting opportunities to study the doublet configuration in detail, in particular the region of natural reversed magnetic shear in the mantle, with a modern complement of diagnostics and under the effect of various heating and current drive systems.

*This work was supported in part by the Swiss National Science Foundation

Presenters

  • Cosmas Heiss

    • Swiss Plasma Center, EPFL
    • EPFL Swiss Plasma Center

Authors

  • Cosmas Heiss

    • Swiss Plasma Center, EPFL
    • EPFL Swiss Plasma Center
  • Federico Felici

    • Google DeepMind
  • Pedro Molina Cabrera

    • Ecole Polytechnique Federale de Lausanne
    • EPFL Swiss Plasma Center
  • Antoine Merle

    • École Normale Supérieure – PSL
    • EPFL Swiss Plasma Center
    • Swiss Plasma Center, EPFL
  • Adriano Mele

    • EPFL Swiss Plasma Center
    • Swiss Plasma Center, EPFL
  • Cristian Galperti

    • EPFL Swiss Plasma Center
    • SPC-EPFL
  • Brendan Tracey

    • Google DeepMind
  • Sarah Bechtle

    • Google DeepMind, London
  • Holger Reimerdes

    • EPFL - Swiss Plasma Center (SPC)
    • EPFL Swiss Plasma Center
    • École Polytechnique Fédérale de Lausanne
  • Olivier Sauter

    • EPFL Swiss Plasma Center
    • EPFL, Swiss Plasma Center (SPC)
    • École Polytechnique Fédérale de Lausanne, Swiss Plasma Center, CH-1015 Lausanne, Switzerland
    • SPC-EPFL
  • Joan Decker

    • Swiss Federal Institute of Technology in Lausanne
  • Stefano Coda

    • Swiss Plasma Center, EPFL
    • Swiss Plasma Center, EPFL, Lausanne
  • Alessandro Balestri

    • Swiss Plasma Center, EPFL
  • Jonas Buchli

    • Deep Mind
  • Francesco Carpanese

    • Ecole Polytechnique Federale de Lausanne
  • Bart De Vylder

    • Google DeepMind, London
  • Craig Donner

    • Google DeepMind
  • Garance Durr-Legoupil-Nicoud

    • EPFL Swiss Plasma Center
    • EPFL - Swiss Plasma Center (SPC)
    • École Polytechnique Fédérale de Lausanne
  • Basil P Duval

    • Ecole Polytechnique Fédérale de Lausanne, SPC
  • Olivier Fevrier

    • EPFL - Swiss Plasma Center (SPC)
    • EPFL Swiss Plasma Center
    • École Polytechnique Fédérale de Lausanne
    • Swiss Plasma Center, EPFL, Lausanne
  • Antonia Frank

    • EPFL Swiss Plasma Center
    • EPFL, Swiss Plasma Center (SPC)
  • Daniele Hamm

    • EPFL Swiss Plasma Center
    • EPFL - Swiss Plasma Center (SPC)
    • EPFL-SPC
  • Philippe Hamel

    • Google DeepMind
  • Ferdinand Hofmann

    • Swiss Plasma Center, EPFL, Lausanne
  • Tyler Jackson

    • Google DeepMind, Montreal
  • Kenneth Lee

    • EPFL - Swiss Plasma Center (SPC)
    • EPFL Swiss Plasma Center
    • EPFL-SPC
  • Tamara Norman

    • Google DeepMind
  • Alessandro Pau

    • EPFL-SPC
  • Francesco Piras

    • Swiss Plasma Center, EPFL, Lausanne
  • Yoeri Poels

    • EPFL-SPC
  • Laurie Porte

    • Ecole Polytechnique Fédérale de Lausanne (EPFL), Swiss Plasma Center (SPC), CH-1015 Lausanne
  • Martin Riedmiller

    • Google DeepMind, London
  • Umar Sheikh

    • Swiss Plasma Center (SPC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,
  • Miguel Silva

    • Swiss Plasma Center, EPFL, Lausanne
  • Joyeeta Sinha

    • Swiss Plasma Center, EPFL, Lausanne
  • Luke Simons

    • EPFL Swiss Plasma Center
    • Ecole Polytechnique Fédérale de Lausanne, SPC
  • Simon Van Mulders

    • EPFL Swiss Plasma Center
  • Benjamin Vincent

    • SPC-EPFL
  • Yinghan Wang

    • Swiss Plasma Center, EPFL, Lausanne