The goal of this project is to formulate and conduct benchmarks which assist in the validation of several computational models developed within the proposed CRC. Here, the main challenge arises from the possibly large uncertainties that are present in the experimental data as well as in the simulation results. A so-called validation metric which compares system response quantities of an experiment with the ones from a computational model has to integrate these uncertainties in a rigorous way. In the proposed project, such validation metrics will be developed by means of a Bayesian validation framework that incorporates parameter and conceptual uncertainty.
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Gzip Archive - 139.8 KB - MD5: 0899b461abd3b1a306bb6170eaa8bb77
DuMux submodule for the extended EICP model.
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Model evaluations for the surrogate and analysis
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Source code for surrogate models and analysis of model results
Oct 1, 2025 - BayesValidRox 2.1.0
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