Bayesian inference; Beams; Copula; Intercorrelated random fields; Intrinsic coregionalization model; Semiparametric latent factor model
Abstract :
[en] Many materials and structures consist of numerous slender struts or fibers. Due to the manufacturing processes of different types of struts and the growth processes of natural fibers, their mechanical response frequently fluctuates from strut to strut, as well as locally within each strut. In associated mechanical models each strut is often represented by a string of beam elements, since the use of conventional three-dimensional finite elements renders the simulations computationally inefficient. The parameter input fields of each string of beam elements are ideally such that the local fluctuations and fluctuations between individual strings of beam elements are accurately captured. The goal of this study is to capture these fluctuations in several intercorrelated bounded random fields. Two formulations to describe the intercorrelations between each random field, as well as the case without any intercorrelation, are investigated. As only a few sets of input fields are available (due to time constraints of the supposed experimental techniques), the identification of the random fields’ parameters involves substantial uncertainties. A probabilistic identification approach based on Bayes’ theorem is employed to treat the involved uncertainties.
Rappel, Hussein; University of Exeter > Engineering ; Alan Turing Institute
Girolami, Mark; University of Cambridge > Engineering ; Alan Turing Institute
Beex, Lars ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
External co-authors :
yes
Language :
English
Title :
Intercorrelated random fields with bounds and the Bayesian identification of their parameters: Application to linear elastic struts and fibers
Publication date :
2022
Journal title :
International Journal for Numerical Methods in Engineering
ISSN :
1097-0207
Publisher :
John Wiley & Sons, Hoboken, United States - New Jersey
Volume :
123
Issue :
15
Pages :
3418-3463
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Computational Sciences
FnR Project :
FNR11501927 - A Virtual Lab For Ni/Pu Hybrid Foams: Stochastic Micromechanical Identification And Efficient Numerical Simulations, 2016 (01/03/2018-28/02/2021) - Lars Beex
Funders :
FNR - Fonds National de la Recherche [LU] Royal Academy of Engineering Lloyds Register Foundation EPSRC - Engineering and Physical Sciences Research Council [GB]