Bayesian calibration and probability bounds analysis solution to the Nasa 2020 UQ challenge on optimization under uncertainty

A. Gray, A. Wimbush, M. DeAngelis, P. O. Hristov, E. Miralles-Dolz, D. Calleja, R. Rocchetta

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)

Samenvatting

Uncertainty quantification is a vital part of all engineering and scientific pursuits. Some of the current most challenging tasks in UQ involve accurately calibrating, propagating and performing optimisation under aleatory and epistemic uncertainty in high dimensional models with very few data; like the challenge proposed by Nasa Langley this year. In this paper we propose a solution which clearly separates aleatory from epistemic uncertainty. A multidimensional 2nd-order distribution was calibrated with Bayesian updating and used as an inner approximation to a p-box. A sliced normal distribution was fit to the posterior, and used to produce cheap samples while keeping the posterior dependence structure. The remaining tasks, such as sensitivity and reliability optimisation, are completed with probability bounds analysis. These tasks were repeated a number of times as designs were improved and more data gathered.

Originele taal-2Engels
Titel30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020
RedacteurenPiero Baraldi, Francesco Di Maio, Enrico Zio
UitgeverijResearch Publishing Services
Pagina's1111-1118
Aantal pagina's8
ISBN van elektronische versie9789811485930
StatusGepubliceerd - 2020
Evenement30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020 - Venice, Virtual, Italië
Duur: 1 nov 20205 nov 2020

Congres

Congres30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020
Land/RegioItalië
StadVenice, Virtual
Periode1/11/205/11/20

Bibliografische nota

Publisher Copyright:
Copyright © ESREL2020-PSAM15 Organizers.Published by Research Publishing, Singapore.

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