Uncertainty Quantification

Uncertainty Quantification

The systematic treatment of uncertainties in the simulation of complex processes is a rapidly growing field. As technical systems are increasingly operated at physical limits, uncertainties due to a lack of knowledge, the manufacturing process and environmental conditions can have an undesirable effect on system behavior. Such uncertainties can be taken into account at an early stage in computer simulations. This is done, for example, by combining stochastic methods with established simulation methods (such as finite elements) and requires interdisciplinary work between the fields of engineering, mathematics/statistics and computer science.

Research topics

• Capturing uncertainties in complex models
• Surrogate modeling, polynomial chaos and kernel methods
• Sensitivity analysis with regard to robustness and reliability
• Methods for Bayesian parameter estimation and inference
• Uncertainty quantification for data-driven simulations
• Applications in mechanics, automotive engineering, aviation