Prof. Bruno Sudret from ETH Zurich visits CRE as Gambrinus Fellowships

The Chair for Reliability Engineering welcomed Prof. Bruno Sudret from ETH Zurich, Switzerland, as a guest between 09th March and 13th March 2026 as part of the Gambrinus Fellowship programme of TU Dortmund University. During his visit, Prof. Sudret delivered a seminar entitled "Structural reliability analysis of nondeterministic systems using stochastic emulators and active learning", on March 10, 2026 at IBZ, TU Dortmund, where he shared his extensive knowledge and experience in Structural Reliability, Uncertainty Quantification, and probabilistic modelling of engineering systems.

In his presentation, Prof. Sudret discussed stochastic simulators, which exhibit intrinsic output variability even for fixed inputs and are increasingly encountered in the modelling of complex engineering systems, such as wind turbines or performance-based engineering under wind or seismic loading. Developing structural reliability methods for such systems, however, remains in its infancy. The talk first formulated the reliability problem for noisy and stochastic simulators and highlighted their distinct nature and implications for reliability analysis. It was shown that brute-force Monte Carlo simulation quickly becomes computationally intractable when estimating failure probabilities for such models.

In the second part of the seminar, Prof. introduced stochastic emulators, and in particular stochastic polynomial chaos expansions (SPCE), which have recently emerged as an appealing surrogate modelling framework that explicitly represents latent model stochasticity. Once calibrated on limited training data, such surrogate models enable the estimation of failure probabilities, albeit at a still significant sampling cost.

Finally, an active learning strategy based on SPCE was presented, which adaptively focuses sampling on regions of the input space where output variability and proximity to failure are most critical. By generating ensembles of plausible SPCE models through likelihood-based sampling of the emulator coefficients, epistemic uncertainty can be quantified and exploited to guide model enrichment. The proposed methodologies were illustrated on analytical benchmark problems as well as on a realistic, data-driven wind turbine reliability assessment.

The CRE team greatly values Prof. Sudret's visit within the Gambrinus Fellowship framework, which promotes international academic exchange at TU Dortmund University, and looks forward to continuing collaboration with him and his team to explore further innovations in structural reliability and uncertainty quantification.

About the Speaker:

Bruno Sudret is a professor of Risk, Safety and Uncertainty quantification at ETH Zurich since 2012. His teaching and research interests are computational methods for uncertainty quantification, reliability and sensitivity analysis, Bayesian approaches for model calibration and reliability-based design optimization, among others. 

He received a master’s of science from the Ecole Polytechnique (France) in 1993. He then obtained a master’s degree and a Ph.D. in civil engineering from the Ecole Nationale des Ponts et Chaussées (France) in 1996 and 1999, respectively. Dr. Sudret has been working in probabilistic engineering mechanics and uncertainty quantification for engineering systems since 2000: first as a post-doctoral fellow at the University of Berkeley (California), then as a researcher at EDF R&D (the French world leader in nuclear power generation) where he was the head of a group specialized in probabilistic engineering mechanics (2001-2008). From 2008 to 2011 he has worked as the Director of Research and Strategy at Phimeca Engineering (France).

Bruno Sudret is the author and co-author of more than 350 publications in journal and conference proceedings. He currently serves in the editorial board of Reliability Engineering and Systems Safety, Probabilistic Engineering Mechanics and Structural Safety. He promotes the dissemination of uncertainty quantification techniques through the development of the software UQLab https://www.uqlab.com and the community platform UQWorld https://uqworld.org.