Efficient uncertainty quantification in stochastic finite element analysis based on functional principal components

DOI10.1007/s00466-015-1185-7zbMath1326.65158OpenAlexW1654366305MaRDI QIDQ498557

Ferdinando Auricchio, Ettore Lanzarone, Ilaria Bianchini, Raffaele Argiento

Publication date: 28 September 2015

Published in: Computational Mechanics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00466-015-1185-7

zbMATH Keywords

finite element analysisfunctional principal component analysisreduced basisoutput uncertainty quantificationstochastic input parameters

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Probabilistic methods, particle methods, etc. for boundary value problems involving PDEs (65N75) Finite element methods applied to problems in solid mechanics (74S05) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30)

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Uses Software

• fda (R)
• spBayes
• FEAPpv

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