On Tuesday, 14th February 2023, Farid Mohammadi, doctoral student at the Department of Hydromechanics and Modelling of Hydrosystems (LH2) and within SFB 1313 will defend his doctoral thesis entitled "A Surrogate-Assisted Bayesian Framework for Uncertainty-Aware Validation Benchmarks".
Date: Tuesday, 14th February 2023
Time: 11:a0 pm
Place: MML, U. 1.003, Pfaffenwaldring 61, 70569 Stuttgart
Abstract
In many modeling tasks, our limited knowledge about the interaction of the governing processes of investigated systems leads to several modeling approaches. These modeling concepts include different levels of detail and different assumptions and can be compared as competing hypotheses in validation benchmarks. In my talk, I will introduce a two-stage Bayesian multi-model framework to help modelers perform uncertainty-aware model validation benchmarks.
To keep the computational costs reasonable, a surrogate model based on polynomial chaos expansion has been used to accelerate the analyses for computationally demanding models. Moreover, I will discuss how surrogate models could benefit from sparse representation and sequential learning to achieve more accurate predictions with as few simulations as the computational budget allows.
The surrogate-assisted uncertainty-aware validation framework was applied to a range of benchmark studies to investigate flow and transport in porous media. It can, however, be applied to other disciplines where models are used to make predictions.
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