The eighty-ninth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, October 30, 2025.
2–3 PM — Edgar Jaber (EDF R&D, Centre Borelli, LISN)
A Bayesian methodology for hybrid degradation prognostics
Degradation prognostics of industrial assets involves estimating their remaining useful life (RUL) by projecting current health indicators and operating conditions while quantifying associated uncertainties. These prognostics are central to the development and deployment of digital twins, which aim to provide insights into the evolving state of complex systems. Traditionally, RUL estimation relies on physics-based simulations or data-driven models. While both have their merits, they can prove inadequate when simulation runtimes are prohibitive or when degradation data is sparse, common challenges in digital twin implementations for critical industrial infrastructure.
To address this problem, we developed an offline modular data assimilation approach. Firstly, a Bayesian model updating strategy combines kernel-based sensitivity analysis to identify and rank the time-varying influence of the model’s input variables, with a tailored inference scheme that accounts for the heterogeneity of available data. Posterior distributions are sampled using MCMC techniques, while the method mitigates the curse of dimensionality by iteratively updating the marginals of influential input variables under an independence assumption. Posterior informativeness is quantified through the Kullback–Leibler divergence, comparing updated distributions to their priors. Secondly, the full state distribution is updated with the help of an ensemble Kalman smoothing step, further reducing the posterior uncertainty.
After detailing the methodology, I will illustrate how this approach enhances the fidelity of RUL predictions and reduces uncertainty in a clogging prognostics use case for digital twins of steam generators in nuclear power plants.
References:
Joint work with Emmanuel Remy (EDF R&D) & Vincent Chabridon (EDF R&D) & Mathilde Mougeot (ENS Paris-Saclay) & Didier Lucor (LISN).
Organizing committee: Pierre Barbillon (MIA-Paris), Julien Bect (L2S), Nicolas Bousquet (EDF R&D), Vincent Chabridon (EDF R&D), Amélie Fau (LMPS), Filippo Gatti (LMPS), Clément Gauchy (CEA), Bertrand Iooss (EDF R&D), Alexandre Janon (LMO), Sidonie Lefebvre (ONERA), Didier Lucor (LISN), Sébastien Petit (LNE), Emmanuel Vazquez (L2S), Xujia Zhu (L2S).
Coordinators: Sidonie Lefebvre (ONERA) & Xujia Zhu (L2S)
Practical details: the seminar will be held online using Microsoft Teams.
If you want to attend this seminar (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay group on Teams, simply send an email and you will be invited. Please specify which email address the invitation must be sent to (this has to be the address associated with your Teams account).
You will find the link to the seminar on the "General" UQSay channel on Teams, approximately 15 minutes before the beginning.
The technical side of things: you can use Teams either directly from your web browser or using the "fat client", which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.
