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An efficient model to predict guided wave radiation by finite-sized sources in multilayered anisotropic plates with account of caustics

Abstract : Elastic guided waves (GW) are used in various non-destructive testing (NDT) methods to inspect plate-like structures, generated by finite-sized transducers. Thanks to GW long range propagation, using a few transducers at permanent positions can provide a full coverage of the plate. Transducer diffraction effects take place, leading to complex radiated fields. Optimizing transducers positioning makes it necessary to accurately predict the GW field radiated by a transducer. Fraunhofer-like approximations applied to GW in isotropic homogeneous plates lead to fast and accurate field computation but can fail when applied to multi-layered anisotropic composite plates, as shown by some examples given. Here, a model is proposed for composite plates, based on the computation of the approximate Green's tensor describing modal propagation from a source point, with account of caustics typically seen when strong anisotropy is concerned. Modal solutions are otherwise obtained by the Semi-Analytic Finite Element method. Transducer diffraction effects are accounted for by means of an angular integration over the transducer surface as seen from the calculation point, that is, over energy paths involved, which are mode-dependent. The model is validated by comparing its predictions with those computed by means of a full convolution integration of the Green's tensor with the source over transducer surface. Examples given concern disk and rectangular shaped transducers commonly used in NDT.
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https://hal-cea.archives-ouvertes.fr/cea-01811899
Contributor : Léna Le Roy <>
Submitted on : Monday, June 11, 2018 - 8:04:05 AM
Last modification on : Tuesday, November 24, 2020 - 2:18:23 PM

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M. Stévenin, A. Lhémery, Sébastien Grondel. An efficient model to predict guided wave radiation by finite-sized sources in multilayered anisotropic plates with account of caustics. Journal of Physics: Conference Series, 2016, 684 (1), ⟨10.1088/1742-6596/684/1/012004⟩. ⟨cea-01811899⟩

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