Farid Mohammadi, Doktorand am Lehrstuhl für Hydromechanik und Hydrosystemmodellierung (LH2) und im SFB 1313 wird am Dienstag, den 14. Februar 2023 seine Doktorarbeit mit dem Titel "A Surrogate-Assisted Bayesian Framework for Uncertainty-Aware Validation Benchmarks" verteidigen.
Datum: Dienstag, 14. Februar 2023
Uhrzeit: 11:00 Uhr
Ort: MML, U. 1.003, Pfaffenwaldring 61, 70569 Stuttgart
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.