Advanced Characterization of Natural Fiber Composites Using Digital Image Correlation

Advanced Characterization of Natural Fiber Composites Using Digital Image Correlation | 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 Research Article Advanced Characterization of Natural Fiber Composites Using Digital Image Correlation K. Sudha Deepthi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5995266/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Composites made from natural fibers have drawn much interest because of their sustainability, lightweight qualities, and capacity to replace synthetic materials in a variety of engineering applications. Nevertheless, their mechanical behavior is still complicated, and precise performance assessment calls for sophisticated characterization methods. This work presents unique approaches to full-field strain and displacement. investigation of natural fiber composites mechanically employing Digital Image Correlation (DIC), a non-contact optical measurement method. The study’s use of DIC allows for the accurate capture of deformation patterns under various loading scenarios, facilitating a thorough knowledge of the fiber-matrix interactions, failure causes, and structural integrity of the composite. The experimental results are evaluated against standard methods, revealing that DIC allows a more complete and accurate evaluation of natural fiber composites’ mechanical properties. This work contributes to the wider use of natural fiber composites in sectors such as construction, automotive, and aerospace by highlighting the potential of digital image correlation (DIC) to improve material testing precision and by suggesting new approaches for optimizing natural fiber composite design. Materials Engineering Natural Fiber composite Digital Image Correlation Banana Fiber Tensile Testing Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5995266","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":413358832,"identity":"bede2f36-0417-459e-a1f2-de5c528a7792","order_by":0,"name":"K. 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