The State of Conservation of Reinforced Concrete Bridges Based on Technical Inspection Data and the GUT Method: A Systematic Literature Review and Case Study

The State of Conservation of Reinforced Concrete Bridges Based on Technical Inspection Data and the GUT Method: A Systematic Literature Review and Case Study | 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 The State of Conservation of Reinforced Concrete Bridges Based on Technical Inspection Data and the GUT Method: A Systematic Literature Review and Case Study Everson Silva, Luiz Fernando, Amâncio Filho, Alberto Casado, Emilia Kohlman, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9170248/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Reinforced concrete bridges are fundamental for mobility and socioeconomic development, but they are subject to deterioration caused by environmental, mechanical, and construction factors. This study conducts a systematic literature review on detrimental manifestations in bridges, addressing inspection methods, structural evaluation, and the use of artificial intelligence in damage detection and prediction. Following the PRISMA protocol, articles published between 2020 and 2026 in national and international databases were analyzed. The results point to an advance in the integration of non-destructive techniques with machine learning models, as well as the application of methodologies such as the GUT method in prioritizing interventions. It is concluded that the combination of traditional approaches and intelligent tools is promising for increasing the efficiency of bridge management and durability. Reinforced concrete bridges Deleterious manifestations Systematic review Structural inspection Artificial intelligence Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 07 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers invited by journal 14 Apr, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 19 Mar, 2026 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-9170248","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626045107,"identity":"6b838c1a-d27f-4439-b3eb-70dbc0929a39","order_by":0,"name":"Everson 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