Surrogates UCL

TN-01_ReportSuitabilityPotentialRomFusionANonIntrusiveRomSolversHighDimensionalOutputs

This report discusses the challenges of efficient uncertainty quantification in modern physical computer models and proposes a non-intrusive reduced order model (ROM) using Gaussian process (GP) surrogates for problems with high dimensional outputs. The method is applied to an anisotropic heat transport problem.

TN-02_ReportSuitabilityPotentialReducedOrderModellingRomFusionModels

This report explores the suitability and potential of Reduced Order Modelling (ROM) in fusion models, specifically focusing on Gaussian Process ROM for Solvers with High-dimensional Outputs.