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Bayesian modelling of the visible spectroscopy reference system at ITER

ORAL

Abstract

In magnetic confinement nuclear fusion devices, spectroscopic diagnostics have been widely employed to extract information on the plasma from its radiation. At ITER, the visible spectroscopy reference system (VSRS) will measure various plasma parameters, for example, the effective ion charge Zeff, electron and ion densities and temperatures, etc. This system will collect different types of plasma radiation including the electron-ion bremsstrahlung continuum and line emission due to excitation, recombination and charge exchange processes along a single horizontal line of sight penetrating the plasma core. The VSRS is modelled within the Minerva framework by taking into account the experimental setup and the relevant physics. This model can generate a synthetic data set according to the ITER operational scenarios and infer the plasma parameters from the generated data set. Based on the model, a real-time algorithm for delivering Zeff with its posterior uncertainties for the ITER's first plasma is developed. This algorithm can also be used to provide a proxy for ne in case of missing line-integrated ne measurements from the interferometer diagnostics for plasma control. The model is implemented in a general way within the IMAS infrastructure and can therefore be applied to similar diagnostics in other IMAS-adapted fusion experiments.

Disclaimer: The views and opinions expressed herein do not necessarily reflect those of the ITER Organization.

Presenters

  • Sehyun Kwak

    Max Planck Institute for Plasma Physics

Authors

  • Sehyun Kwak

    Max Planck Institute for Plasma Physics

  • Maarten De Bock

    ITER Organization

  • Maciej Krychowiak

    Max Planck Institute for Plasma Physics

  • Ralf König

    Max Planck Institute for Plasma Physics, Max-Planck-Institut für Plasmaphysik

  • Jakob Svensson

    Max Planck Institute for Plasma Physics

  • Thomas Sunn S Pedersen

    Max Planck Institute for Plasma Physics, IPP