CEMRACS - Summer school: Numerical methods for stochastic models: control, uncertainty quantification, mean-field / CEMRACS - École d'été : Méthodes numériques pour équations stochastiques : contrôle, incertitude, champ moyen

Collection CEMRACS - Summer school: Numerical methods for stochastic models: control, uncertainty quantification, mean-field / CEMRACS - École d'été : Méthodes numériques pour équations stochastiques : contrôle, incertitude, champ moyen

Organizer(s) Bouchard, Bruno ; Chassagneux, Jean-François ; Delarue, François ; Gobet, Emmanuel ; Lelong, Jérôme

Date(s) 17/07/2017 - 25/08/2017

linked URL http://conferences.cirm-math.fr/1556.html

00:00:00 / 00:00:00

25 31

Metamodels for uncertainty quantification and reliability analysis

By Stefano Marelli

Also appears in collection : Ecoles de recherche

Uncertainty quantification (UQ) in the context of engineering applications aims aims at quantifying the effects of uncertainty in the input parameters of complex models on their output responses. Due to the increased availability of computational power and advanced modelling techniques, current simulation tools can provide unprecedented insight in the behaviour of complex systems. However, the associated computational costs have also increased significantly, often hindering the applicability of standard UQ techniques based on Monte-Carlo sampling. To overcome this limitation, metamodels (also referred to as surrogate models) have become a staple tool in the Engineering UQ community. This lecture will introduce a general framework for dealing with uncertainty in the presence of expensive computational models, in particular for reliability analysis (also known as rare event estimation). Reliability analysis focuses on the tail behaviour of a stochastic model response, so as to compute the probability of exceedance of a given performance measure, that would result in a critical failure of the system under study. Classical approximation-based techniques, as well as their modern metamodel-based counter-parts will be introduced.

Information about the video

Date of recording 21/07/2017
Date of publication 01/08/2017
Institution CIRM
Licence CC BY NC ND
Language English
Audience Researchers, Graduate Students
Director(s) Guillaume Hennenfent
Format MP4

Citation data

DOI 10.24350/CIRM.V.19201603
Cite this video Marelli, Stefano (21/07/2017). Metamodels for uncertainty quantification and reliability analysis. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19201603
URL https://dx.doi.org/10.24350/CIRM.V.19201603

Domain(s)

MSC codes

Document(s)

http://smai.emath.fr/cemracs/cemracs17/Slides/marelli.pdf

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