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Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

  • JET Contributors
  • , the ASDEX Upgrade, MAST and TCV Teams
  • Commissariat à l’énergie atomique et aux énergies alternatives
  • Swiss Federal Institute of Technology Lausanne
  • Max Planck Institute for Plasma Physics
  • VTT Technical Research Centre of Finland Ltd.
  • National Research Council of Italy
  • Czech Academy of Sciences
  • University of Lisbon
  • University of Naples Federico II
  • University of Cagliari
  • University of Naples Parthenope
  • Agenzia nazionale per le nuove tecnologie, l'energia e lo sviluppo economico sostenibile
  • National Technical University of Athens
  • CIEMAT
  • University of Oxford
  • United Kingdom Atomic Energy Authority
  • EUROfusion PMU
  • University of Seville
  • Wigner Research Centre for Physics
  • Eindhoven University of Technology
  • University of Strathclyde
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  • Aix-Marseille University
  • University of Rome Tor Vergata
  • Uppsala University
  • University of Warwick
  • Andrzej Soltan Institute for Nuclear Studies
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  • J. Stefan Institute
  • University of York
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Research output: Contribution to journalArticlepeer-review

62 Citations (Scopus)

Abstract

The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of T e, T i and n e have been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks.

Original languageEnglish
Article number096006
JournalNuclear Fusion
Volume58
Issue number9
DOIs
Publication statusPublished - 3 Jul 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • integrated tokamak simulation
  • machine learning
  • real-time control
  • tokamak profiles
  • tokamak transport

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