Bayesian Integrated Data Analysis of Fast-Ion Measurements by Velocity-Space Tomography

Tutkimustuotos: Lehtiartikkeli

Tutkijat

  • M. Salewski
  • M. Nocente
  • A. S. Jacobsen
  • F. Binda
  • C. Cazzaniga
  • J. Eriksson
  • B. Geiger
  • G. Gorini
  • C. Hellesen
  • V. G. Kiptily
  • T. Koskela
  • S. B. Korsholm
  • F. Leipold
  • D. Moseev
  • S. K. Nielsen
  • J. Rasmussen
  • P. A. Schneider
  • S. E. Sharapov
  • M. Stejner
  • M. Tardocchi
  • JET Contributors
  • ASDEX Upgrade Team
  • EUROfusion MST1 Team

Organisaatiot

  • Danmarks Tekniske Universitet
  • CNR-ENEA-EURATOM Association
  • Max-Planck-Institut für Plasmaphysik
  • Uppsala University
  • Rutherford Appleton Laboratory
  • JET
  • Lawrence Berkeley National Laboratory

Kuvaus

Bayesian integrated data analysis combines measurements from different diagnostics to jointly measure plasma parameters of interest such as temperatures, densities, and drift velocities. Integrated data analysis of fast-ion measurements has long been hampered by the complexity of the strongly non-Maxwellian fast-ion distribution functions. This has recently been overcome by velocity-space tomography. In this method two-dimensional images of the velocity distribution functions consisting of a few hundreds or thousands of pixels are reconstructed using the available fast-ion measurements. Here we present an overview and current status of this emerging technique at the ASDEX Upgrade tokamak and the JET toamak based on fast-ion D-alpha spectroscopy, collective Thomson scattering, gamma-ray and neutron emission spectrometry, and neutral particle analyzers. We discuss Tikhonov regularization within the Bayesian framework. The implementation for different types of diagnostics as well as the uncertainties are discussed, and we highlight the importance of integrated data analysis of all available detectors.

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut23-36
Sivumäärä14
JulkaisuFusion Science and Technology
Vuosikerta74
Numero1-2
TilaJulkaistu - 2018
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

ID: 26482752