Bayesian characterization of Young's modulus of viscoelastic materials in laminated structures
| Autor: | Mohamed Ali Hamdi, Erliang Zhang, Jean-Daniel Chazot, Jérôme Antoni |
|---|---|
| Přispěvatelé: | Roberval (Roberval), Université de Technologie de Compiègne (UTC), Laboratoire Vibrations Acoustique (LVA), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA) |
| Rok vydání: | 2013 |
| Předmět: |
[SPI.ACOU]Engineering Sciences [physics]/Acoustics [physics.class-ph]
Mathematical optimization Acoustics and Ultrasonics Mechanical Engineering Bayesian probability Probabilistic logic Modulus Young's modulus 02 engineering and technology Condensed Matter Physics 01 natural sciences Viscoelasticity [PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph] Fractional calculus symbols.namesake 020303 mechanical engineering & transports Surrogate model 0203 mechanical engineering Mechanics of Materials 0103 physical sciences symbols Applied mathematics Laminated glass 010301 acoustics Mathematics |
| Zdroj: | Journal of Sound and Vibration Journal of Sound and Vibration, Elsevier, 2013, 332 (16), pp.3654-3666. ⟨10.1016/j.jsv.2013.02.032⟩ |
| ISSN: | 0022-460X 1095-8568 |
| Popis: | International audience; This paper addresses an inverse approach to estimate the frequency-dependent Young's modulus of a viscoelastic polymer layer in 4 laminated structure. The Young's modulus is parameterized by a fractional derivative model and examined from a Bayesian perspective with the consideration of measurement and modeling uncertainties. The probabilistic Bayesian identification is carried out based on an efficient surrogate model through the use of Markov Chain Monte Carlo sampling methods. The proposed approach is experimentally validated on laminated glass. (C) 2013 Elsevier Ltd. All rights reserved. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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