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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.

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

    EPFL Swiss Plasma Center, Ecole Polytechnique Federale de Lausanne

  • Antoine Merle

    Swiss Plasma Center, EPFL, EPFL Swiss Plasma Center, École Normale Supérieure – PSL

  • 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

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

  • Joan Decker

    Swiss Federal Institute of Technology in Lausanne

  • Stefano Coda

    Swiss Plasma Center, EPFL, Lausanne, Swiss Plasma Center, EPFL

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

  • Basil P Duval

    Ecole Polytechnique Fédérale de Lausanne, SPC

  • Olivier Fevrier

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

  • Antonia Frank

    EPFL Swiss Plasma Center, EPFL, Swiss Plasma Center (SPC)

  • Daniele Hamm

    EPFL - Swiss Plasma Center (SPC), EPFL Swiss Plasma Center, 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