Abstract

The use of Lamb waves within a guided wave (GW)–based scheme holds promise toward monitoring and nondestructive evaluation (NDE) of plate structures. Their short wavelength enables interaction with small defects and they can travel long distances, thus offering extensive spatial coverage. In boosting the performance of these schemes for more advanced damage identification tasks, such as precise damage localization and quantification, the fusion of measurement data with models is advantageous. Such a hybrid scheme, which relies on the inclusion of engineering models, is hampered by the short wavelengths of GW-based schemes. Short wavelengths require a fine discretization of numerical models in space and in time, which results in high computational costs. In alleviating this issue, we propose a reduced-order model (ROM) relying on exploitation of the frequency response function (FRF) principle, which is parameterized with respect to the positioning of local defects. Through appropriate coordinate transformations, the surrogate, constructed based on the matching pursuit (MP) algorithm, can exploit the mechanical properties of the wave so that only a small amount of training simulations are needed. The efficacy of the proposed surrogate is demonstrated in a synthetic inverse setting, using a particle swarm optimization (PSO) strategy.

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Data Availability Statement

No data, models, or code were generated or used during the study.

Acknowledgments

This research is conducted as part of the project “Fusion of Models and Data for Enriched Evaluation of Structural Health” financed by the National Science Center (Poland) and the Swiss National Science Foundation (200021L_192139). Dr. Soman acknowledges the support of the National Science Center, Poland, for developing the PSO through the project 2019/33/ST8/01699.

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Journal of Engineering Mechanics
Volume 150Issue 9September 2024

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Received: Dec 22, 2023
Accepted: Mar 25, 2024
Published online: Jun 27, 2024
Published in print: Sep 1, 2024
Discussion open until: Nov 27, 2024

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Ph.D. Candidate, Institute of Structural Engineering, ETH Zurich, Stefano-Franscini-Platz 5, Zurich 8093, Switzerland. ORCID: https://orcid.org/0000-0003-4632-7079. Email: [email protected]
Senior Lecturer, Dept. of Engineering, Faculty of Environment, Science and Economy, Univ. of Exeter, North Park Rd., Exeter EX4 4QF, UK. ORCID: https://orcid.org/0000-0002-9556-417X. Email: [email protected]
Assistant Professor, Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Fiszera 14, Gdansk 80-231, Poland. ORCID: https://orcid.org/0000-0002-5499-2565. Email: [email protected]
Professor and Head of the Mechanics of Intelligent Structures Dept., Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Fiszera 14, Gdansk 80-231, Poland. ORCID: https://orcid.org/0000-0002-8061-8614. Email: [email protected]
Associate Professor, Institute of Structural Engineering, ETH Zurich, Stefano-Franscini-Platz 5, Zurich 8093, Switzerland (corresponding author). ORCID: https://orcid.org/0000-0002-6870-240X. Email: [email protected]

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