Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Azizi, Victor, Smeets, Stef, Koechl, Florian, Casson, Francis, Citrin, Jonathan, Ho, Aaron
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2409.13529
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866912195781066752
author Azizi, Victor
Smeets, Stef
Koechl, Florian
Casson, Francis
Citrin, Jonathan
Ho, Aaron
author_facet Azizi, Victor
Smeets, Stef
Koechl, Florian
Casson, Francis
Citrin, Jonathan
Ho, Aaron
contents Large scale validation and uncertainty quantification are essential in the experimental design, control, and operations of fusion reactors. Reduced models and increasing computational power means that it is possible to run many simulations, yet setting up simulation runs remaining a time-consuming and error-prone process that involves many manual steps. duqtools is an open-source workflow tool written in Python for that addresses this bottleneck by automating the set up of new simulations. This enables uncertainty quantification and large scale validation of fusion energy modelling simulations. In this work, we demonstrate how duqtools can be used to set up and launch 2000 different simulations of plasma experiments to validate aspects of the JINTRAC modelling suite. With this large-scale validation we identified issues in preserving data consistency in model initialization of the current ($I(p)$) distribution. Furthermore, we used duqtools for sensitivity analysis on the QLKNN-jetexp-15D surrogate model to verify its correctness in multiple regimes.
format Preprint
id arxiv_https___arxiv_org_abs_2409_13529
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Duqtools: Dynamic uncertainty quantification for Tokamak reactor simulations modelling
Azizi, Victor
Smeets, Stef
Koechl, Florian
Casson, Francis
Citrin, Jonathan
Ho, Aaron
Plasma Physics
Large scale validation and uncertainty quantification are essential in the experimental design, control, and operations of fusion reactors. Reduced models and increasing computational power means that it is possible to run many simulations, yet setting up simulation runs remaining a time-consuming and error-prone process that involves many manual steps. duqtools is an open-source workflow tool written in Python for that addresses this bottleneck by automating the set up of new simulations. This enables uncertainty quantification and large scale validation of fusion energy modelling simulations. In this work, we demonstrate how duqtools can be used to set up and launch 2000 different simulations of plasma experiments to validate aspects of the JINTRAC modelling suite. With this large-scale validation we identified issues in preserving data consistency in model initialization of the current ($I(p)$) distribution. Furthermore, we used duqtools for sensitivity analysis on the QLKNN-jetexp-15D surrogate model to verify its correctness in multiple regimes.
title Duqtools: Dynamic uncertainty quantification for Tokamak reactor simulations modelling
topic Plasma Physics
url https://arxiv.org/abs/2409.13529