Turbulent transport model validation against a JET plasma via integrated modelling enhanced by Gaussian process regression

Turbulent transport model validation against a JET plasma via integrated modelling enhanced by Gaussian process regression

Turbulent transport model validation against a JET plasma via integrated modelling enhanced by Gaussian process regression 150 150 UKAEA Opendata
UKAEA-CCFE-PR(19)10

Turbulent transport model validation against a JET plasma via integrated modelling enhanced by Gaussian process regression

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. This allows for rigourous sensitivity tests of prescribed initial and boundary conditions, as GPR fitting provides both fit and derivative uncertainties. This was demonstrated by a JETTO integrated modelling simulation of the JET ITERlike-wall H-mode baseline discharge #92436 with the QuaLiKiz quasilinear turbulent transport model.

Collection:
Journals
Journal:
Nuclear Fusion
Publisher:
IOP (Institute of Physics)
Published date:
05/12/2021