MS 5: On-the-fly Model Modification, Error Control, and Simulation Adaptivity


Organizers & Moderation
Bernd Flemisch
Marco Oesting

Large-scale simulations of complex systems aim at achieving (1) high accuracy in terms of systematic errors, (2) high precision in terms of stochastic errors and (3) an efficient use of limited resources in terms of computational power and available data. The competing nature of these objectives requires trade-offs within the triangle spanned by the three targets (1)-(3). In this mini-symposium, we will explore recent advances in handling these trade-offs. In particular, the talks will cover topics in classical scientific computing (accuracy vs. resources), uncertainty quantification (precision vs. resources) and stochastic modeling (precision vs. accuracy).

Thursday, 5 October 2023, 4:00-5:30 pm

Simulation Research Highlights in the Triangle between Resource Limitations, Accuracy and Precision

Ivan Buntic, Arthur Günthner, Felix Huber, Oliver König, Cedric Riethmüller, Max Thannheimer 
(University of Stuttgart)

4:00 - 4:30 pm

An introduction to surrogate modelling for uncertainty quantification in computational sciences Bruno Sudret
(ETH Zürich)
4:30 - 4:50 pm
Balancing Statistical and Computational Precision Johannes Lederer
(Ruhr-Universität Bochum)
4:50 - 5:10 pm
Nonlinear projections for structure preservation and conserved
quantities in Neural Galerkin schemes
Paul Schwerdtner
(New York University)
5:10 - 5:30 pm
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