UM
A fast Bayesian inference scheme for identification of local structural properties of layered composites based on wave and finite element-assisted metamodeling strategy and ultrasound measurements
Yan,Wang Ji1; Chronopoulos,Dimitrios2; Cantero-Chinchilla,Sergio2,3; Yuen,Ka Veng1; Papadimitriou,Costas4
2020-09-01
Source PublicationMechanical Systems and Signal Processing
ISSN0888-3270
Volume143
AbstractReliable verification and evaluation of the mechanical properties of a layered composite ensemble are critical for industrially relevant applications, however it still remains an open engineering challenge. In this study, a fast Bayesian inference scheme based on multi-frequency single shot measurements of wave propagation characteristics is developed to overcome the limitations of ill-conditioning and non-uniqueness associated with the conventional approaches. A Transitional Markov chain Monte Carlo (TMCMC) algorithm is employed for the sampling process. A Wave and Finite Element (WFE)-assisted metamodeling scheme in lieu of expensive-to-evaluate explicit FE analysis is proposed to cope with the high computational cost involved in TMCMC sampling. For this, the Kriging predictor providing a surrogate mapping between the probability spaces of the model predictions for the wave characteristics and the mechanical properties in the likelihood evaluations is established based on the training outputs computed using a WFE forward solver, coupling periodic structure theory to conventional FE. The valuable uncertainty information of the prediction variance introduced by the use of a surrogate model is also properly taken into account when estimating the parameters’ posterior probability distribution by TMCMC. A numerical study as well as an experimental study are conducted to verify the computational efficiency and accuracy of the proposed methodology. Results show that the TMCMC algorithm in conjunction with the WFE forward solver-aided metamodeling can sample the posterior Probability Density Function (PDF) of the updated parameters at a very reasonable cost. This approach is capable of quantifying the uncertainties of recovered independent characteristics for each layer of the composite structure under investigation through fast and inexpensive experimental measurements on localized portions of the structure.
KeywordBayesian analysis Composite structure Metamodeling Ultrasonic guided waves Uncertainty quantification Wave and finite element
DOI10.1016/j.ymssp.2020.106802
URLView the original
Language英语
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Cited Times [WOS]:5   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering,University of Macau,China
2.Institute for Aerospace Technology & The Composites Group,The University of Nottingham,United Kingdom
3.Aernnova Engineering Division S.A.,Madrid,28034,Spain
4.Department of Mechanical Engineering,University of Thessaly,Greece
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yan,Wang Ji,Chronopoulos,Dimitrios,Cantero-Chinchilla,Sergio,et al. A fast Bayesian inference scheme for identification of local structural properties of layered composites based on wave and finite element-assisted metamodeling strategy and ultrasound measurements[J]. Mechanical Systems and Signal Processing,2020,143.
APA Yan,Wang Ji,Chronopoulos,Dimitrios,Cantero-Chinchilla,Sergio,Yuen,Ka Veng,&Papadimitriou,Costas.(2020).A fast Bayesian inference scheme for identification of local structural properties of layered composites based on wave and finite element-assisted metamodeling strategy and ultrasound measurements.Mechanical Systems and Signal Processing,143.
MLA Yan,Wang Ji,et al."A fast Bayesian inference scheme for identification of local structural properties of layered composites based on wave and finite element-assisted metamodeling strategy and ultrasound measurements".Mechanical Systems and Signal Processing 143(2020).
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