uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Application of Gaussian process regression to plasma turbulent transport model validation via integrated modelling
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
Show others and affiliations
Number of Authors: 12312019 (English)In: Nuclear Fusion, ISSN 0029-5515, E-ISSN 1741-4326, Vol. 59, no 5, article id 056007Article in journal (Refereed) Published
Abstract [en]

This paper outlines an approach towards improved rigour in tokamak turbulence transport model validation within integrated modelling. Gaussian process regression (GPR) techniques were applied for profile fitting during the preparation of integrated modelling simulations allowing for rigourous sensitivity tests of prescribed initial and boundary conditions as both fit and derivative uncertainties are provided. This was demonstrated by a JETTO integrated modelling simulation of the JET ITER-like-wall H-mode baseline discharge #92436 with the QuaLiKiz quasilinear turbulent transport model, which is the subject of extrapolation towards a deuterium-tritium plasma. The simulation simultaneously evaluates the time evolution of heat, particle, and momentum fluxes over similar to 10 confinement times, with a simulation boundary condition at rho(tor) = 0.85. Routine inclusion of momentum transport prediction in multi-channel flux-driven transport modelling is not standard and is facilitated here by recent developments within the QuaLiKiz model. Excellent agreement was achieved between the fitted and simulated profiles for n(e), T-e, T-i, and Omega(tor) within 2 sigma, but the simulation underpredicts the mid-radius Ti and overpredicts the core n(e) and T-e profiles for this discharge. Despite this, it was shown that this approach is capable of deriving reasonable inputs, including derivative quantities, to tokamak models from experimental data. Furthermore, multiple figures-of-merit were defined to quantitatively assess the agreement of integrated modelling predictions to experimental data within the GPR profile fitting framework.

Place, publisher, year, edition, pages
IOP PUBLISHING LTD , 2019. Vol. 59, no 5, article id 056007
Keywords [en]
tokamak, turbulence, model validation, integrated modelling, uncertainty quantification, gaussian processes
National Category
Fusion, Plasma and Space Physics
Identifiers
URN: urn:nbn:se:uu:diva-398662DOI: 10.1088/1741-4326/ab065aISI: 000462112700004OAI: oai:DiVA.org:uu-398662DiVA, id: diva2:1379671
Note

For complete list of authors see http://dx.doi.org/10.1088/1741-4326/ab065a

Available from: 2019-12-17 Created: 2019-12-17 Last updated: 2019-12-17Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Andersson Sundén, ErikCecconello, MarcoConroy, SeanEricsson, GöranEriksson, JacobHjalmarsson, AndersPossnert, GöranSjöstrand, HenrikWeiszflog, Matthias

Search in DiVA

By author/editor
Andersson Sundén, ErikCecconello, MarcoConroy, SeanEricsson, GöranEriksson, JacobHjalmarsson, AndersPossnert, GöranSjöstrand, HenrikWeiszflog, Matthias
By organisation
Applied Nuclear PhysicsTandem Laboratory
In the same journal
Nuclear Fusion
Fusion, Plasma and Space Physics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf