A Hybrid Theoretical-Numerical-Experimental Framework for Robust Health Monitoring of Thin-Walled Hollow Composite Members using Guided Waves 

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A Hybrid Theoretical-Numerical-Experimental Framework for Robust Health Monitoring of Thin-Walled Hollow Composite Members using Guided Waves | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A Hybrid Theoretical-Numerical-Experimental Framework for Robust Health Monitoring of Thin-Walled Hollow Composite Members using Guided Waves Akshay Prakash Kalgutkar, Shirsendu Sikdar, Sauvik Banerjee, Karl Walton, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5232576/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Thin-walled hollow composite members (HCM) are extensively employed in aerospace and automotive industries due to their high strength-to-weight ratio and design flexibility. This study introduces a hybrid theoretical-numerical-experimental framework for robust detection and characterisation of barely visible damage in HCM using guided waves (GW). It focuses on assessing surface abrasion and hairline cracks, two common yet challenging damage types encountered in the field. A semi-analytical finite element (SAFE) formulation is developed for the dispersion analysis alongside numerical simulations using finite element software COMSOL Multiphysics, and experimental validation is performed to ensure accurate and reliable results. The study focuses on GW propagation and scattering behaviour under varying damage scenarios, exploring the effects of damage size, position, and its offset on wave features. Parametric analyses show significant variations in wave characteristics such as group velocity, amplitude, amongst other mode features. A waveform and statistical approach incorporating continuous wavelet transform and energy enables precise damage classification. Results show that abrasion-induced damages cause substantial changes in GW features in terms of DIs and statistical parameters, while hairline cracks marginally affect the damage indices and wave features, aiding in distinguishing between different damage types. These findings contribute to the development of robust damage identification algorithms for structural health monitoring, providing valuable insights for optimising the maintenance and performance of composite structures in critical engineering environments, ensuring safety and operational efficiency. Physical sciences/Engineering Physical sciences/Engineering/Aerospace engineering Hollow composite member guided wave surface abrasion hairline crack structural health monitoring Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 11 Dec, 2024 Reviews received at journal 10 Dec, 2024 Reviewers agreed at journal 03 Nov, 2024 Reviews received at journal 02 Nov, 2024 Reviewers agreed at journal 31 Oct, 2024 Reviewers invited by journal 28 Oct, 2024 Editor assigned by journal 28 Oct, 2024 Editor invited by journal 25 Oct, 2024 Submission checks completed at journal 24 Oct, 2024 First submitted to journal 09 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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