English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper outlines an approach towards improved rigour in tokamak turbulencetransport model validation within integrated modelling. Gaussian processregression (GPR) techniques were applied for profile fitting during thepreparation of integrated modelling simulations allowing for rigouroussensitivity tests of prescribed initial and boundary conditions as both fit andderivative uncertainties are provided. This was demonstrated by a JETTOintegrated modelling simulation of the JET ITER-like-wall H-mode baselinedischarge #92436 with the QuaLiKiz quasilinear turbulent transport model, whichis the subject of extrapolation towards a deuterium-tritium plasma. Thesimulation simultaneously evaluates the time evolution of heat, particle, andmomentum fluxes over $\sim10$ confinement times, with a simulation boundarycondition at $\rho_{tor} = 0.85$. Routine inclusion of momentum transportprediction in multi-channel flux-driven transport modelling is not standard andis facilitated here by recent developments within the QuaLiKiz model. Excellentagreement was achieved between the fitted and simulated profiles for $n_e$,$T_e$, $T_i$, and $\Omega_{tor}$ within $2\sigma$, but the simulationunderpredicts the mid-radius $T_i$ and overpredicts the core $n_e$ and $T_e$profiles for this discharge. Despite this, it was shown that this approach iscapable of deriving reasonable inputs, including derivative quantities, totokamak models from experimental data. Furthermore, multiple figures-of-meritwere defined to quantitatively assess the agreement of integrated modellingpredictions to experimental data within the GPR profile fitting framework.

Application of Gaussian process regression to plasma turbulent transport model validation via integrated modelling