Time-dependent seismic vulnerability of coastal bridges under temperature-humidity-driven chloride damage

Time-dependent seismic vulnerability of coastal bridges under temperature-humidity-driven chloride damage | 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 Time-dependent seismic vulnerability of coastal bridges under temperature-humidity-driven chloride damage Guojun Yang, Shenghai Liu, Pengbo Sun, Chunming Hou, Yongfeng Du This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8977087/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract This study presents a time-dependent seismic vulnerability assessment framework for coastal bridges exposed to temperature, humidity, and chloride-induced corrosion. A modified three-dimensional chloride diffusion model incorporating temperature, humidity, and time correction factors is developed to simulate chloride transport in concrete and predict corrosion initiation and propagation. Corrosion-induced material degradation, including reinforcement cross-section loss, yield strength reduction, and concrete cover cracking, is explicitly modeled in a nonlinear finite-element bridge model. Incremental dynamic analysis is conducted at multiple service ages to derive time-varying seismic fragility curves. To enable efficient assessment, a stacking-based machine learning model is proposed for rapid seismic vulnerability prediction. Results indicate that elevated temperature and humidity significantly accelerate chloride penetration and reinforcement corrosion, leading to pronounced reductions in seismic performance, particularly due to longitudinal reinforcement deterioration. Corrosion markedly increases the probability of severe and complete damage under moderate and strong earthquakes, while concrete cover degradation and reduced stirrup confinement further exacerbate vulnerability. The stacking model achieves high accuracy and efficiency, with close agreement to numerical results (minimum R² = 0.896, maximum MAE = 0.113, maximum RMSE = 0.126). The proposed framework provides practical guidance for durability-oriented design, seismic risk assessment, and maintenance planning of coastal bridges in aggressive marine environments. Temperature humidity Chloride ingress Reinforcement corrosion Time-dependent seismic vulnerability Incremental Dynamic Analysis Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 21 Mar, 2026 Reviewers invited by journal 18 Mar, 2026 Editor invited by journal 18 Mar, 2026 Editor assigned by journal 03 Mar, 2026 First submitted to journal 27 Feb, 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-8977087","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":608173795,"identity":"6b1d204d-370a-4eea-ba58-6c35593f2d8e","order_by":0,"name":"Guojun Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYNACHjYeefbGxocfSNDCJ2fYc7jZWIIEa+SMGW6ktwnwEKPW4PjZwy+/yJglNs582MYgwWAnp9tASMuZvDRrGZ60xHbpxLYHBQzJxmYHCGk5kGNmLMFzLLFxdmK7gQTDgcRtBLWcfwPS8j+x4ebBNgkeorTcyDF++IGHDeh9RiK1SN54Y8YMjBdgICcCA9mACL/wnc8x/vizBxSVxx8+/FBhJ0dQi8IBBjZp3h64OwkoBwH5Bgbmjz9+EKFyFIyCUTAKRi4AAM1cRY0DUuXiAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2203-3183","institution":"Lanzhou University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Guojun","middleName":"","lastName":"Yang","suffix":""},{"id":608173796,"identity":"06421245-b670-43b2-b683-e5a175ec9212","order_by":1,"name":"Shenghai Liu","email":"","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Shenghai","middleName":"","lastName":"Liu","suffix":""},{"id":608173797,"identity":"f2415b23-a678-4750-adbd-d016e0b39d91","order_by":2,"name":"Pengbo Sun","email":"","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Pengbo","middleName":"","lastName":"Sun","suffix":""},{"id":608173798,"identity":"52a15298-ad94-4469-bdab-b18578696ccd","order_by":3,"name":"Chunming Hou","email":"","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Chunming","middleName":"","lastName":"Hou","suffix":""},{"id":608173799,"identity":"8396ad70-7ae5-46de-8838-6ba6ddc59f78","order_by":4,"name":"Yongfeng Du","email":"","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yongfeng","middleName":"","lastName":"Du","suffix":""}],"badges":[],"createdAt":"2026-02-26 11:14:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8977087/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8977087/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105092789,"identity":"135028d3-59d7-49ce-a130-62a4d9a31be5","added_by":"auto","created_at":"2026-03-21 01:13:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1837386,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8977087/v1_covered_14bce569-cb79-44ac-8248-b70400501c50.pdf"}],"financialInterests":"","formattedTitle":"Time-dependent seismic vulnerability of coastal bridges under temperature-humidity-driven chloride damage","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bulletin-of-earthquake-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"beee","sideBox":"Learn more about [Bulletin of Earthquake Engineering](https://www.springer.com/journal/10518)","snPcode":"10518","submissionUrl":"https://submission.nature.com/new-submission/10518/3","title":"Bulletin of Earthquake Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Temperature, humidity, Chloride ingress, Reinforcement corrosion, Time-dependent seismic vulnerability, Incremental Dynamic Analysis","lastPublishedDoi":"10.21203/rs.3.rs-8977087/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8977087/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study presents a time-dependent seismic vulnerability assessment framework for coastal bridges exposed to temperature, humidity, and chloride-induced corrosion. A modified three-dimensional chloride diffusion model incorporating temperature, humidity, and time correction factors is developed to simulate chloride transport in concrete and predict corrosion initiation and propagation. Corrosion-induced material degradation, including reinforcement cross-section loss, yield strength reduction, and concrete cover cracking, is explicitly modeled in a nonlinear finite-element bridge model. Incremental dynamic analysis is conducted at multiple service ages to derive time-varying seismic fragility curves. To enable efficient assessment, a stacking-based machine learning model is proposed for rapid seismic vulnerability prediction. Results indicate that elevated temperature and humidity significantly accelerate chloride penetration and reinforcement corrosion, leading to pronounced reductions in seismic performance, particularly due to longitudinal reinforcement deterioration. Corrosion markedly increases the probability of severe and complete damage under moderate and strong earthquakes, while concrete cover degradation and reduced stirrup confinement further exacerbate vulnerability. The stacking model achieves high accuracy and efficiency, with close agreement to numerical results (minimum R\u0026sup2; = 0.896, maximum MAE\u0026thinsp;=\u0026thinsp;0.113, maximum RMSE\u0026thinsp;=\u0026thinsp;0.126). 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