The eighty-second UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, January 30, 2025.
2-3 PM — Alexandros A. Taflanidis (University of Notre Dame, Department of Civil and Environmental Engineering and Earth Sciences, USA) — [slides]
Reduced order and surrogate modeling applications for computationally efficient uncertainty propagation within seismic vulnerability assessment
Seismic vulnerability assessment involves the quantification and propagation of the different courses of uncertainty impacting structural performance. For engineering demand parameters (EDPs) the relevant uncertainties pertain to the seismic hazard and/or to the structural model characteristics, while the detailed characterization of structural vulnerability is typically performed using nonlinear response-history analysis (NLRHA). Despite recent advances in computational science, the adoption of computationally intensive, high-fidelity finite element models (FEMs) for performing NLRHA remains a challenge for many seismic risk assessment applications, forcing some sort of simplification of the uncertainty characterization. This presentation will investigate two alternative computational statistics approaches for improving computational efficiency in such settings.
The first approach will be the use of reduced order models (ROMs), coupled, if needed, with a Multi-Fidelity Monte Carlo (MFMC) implementation. ROMs simplify the physics-based description of the original FEM through some form of condensation of the degrees of freedom and equations of motion, coupled with an approximation of the nonlinear (hysteretic) response characteristics. In order to accommodate any potential bias from the ROM approximation, a MFMC setting is additionally examined. In the latter setting, the ROM serves as a means to accelerate the Monte Carlo convergence, relying ultimately on the FEM to establish unbiased predictions.
The second approach will be the use of surrogate models, offering an entirely data-driven mathematical approximation of the input/output relationships of the high-fidelity model. For addressing aleatoric uncertainties in the hazard description (i.e., the so-called ground-motion to ground-motion variability), a stochastic Gaussian Process (GP) emulation approach is adopted to directly approximate the EDP distribution (considering the influence of the aleatoric uncertainties). Improvements in computational efficiency are promoted by avoiding any replications for the stochastic GP implementation. The extension to vector EDP outputs is also briefly discussed, accommodated by approximating the correlation matrix.
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.
