Bearing Capacity Prediction of Lightweight Steel Double L-Joints Based on Experimental Investigation and an Improved Gaussian Process Regression Algorithm

Bearing Capacity Prediction of Lightweight Steel Double L-Joints Based on Experimental Investigation and an Improved Gaussian Process Regression Algorithm | 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 Bearing Capacity Prediction of Lightweight Steel Double L-Joints Based on Experimental Investigation and an Improved Gaussian Process Regression Algorithm Ding Wei, Jia Suizi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8811407/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 The vertical load-bearing capacity of earthquake-damaged prefabricated frame structures determines their ability to resist collapse during aftershocks. In particular, the response performance of the beam-column joint area of prefabricated frame structures to axial compression after earthquake damage plays a key role in determining the vertical load-bearing capacity of the structure. To study the bearing capacity of beam-column joints in post-earthquake prefabricated light steel frames, firstly, based on nine existing low-cycle repeated loading tests of beam-column joints in different structural prefabricated light steel frames, axial compression performance tests were conducted on nine joints with different degrees of damage and different structures by applying axial forces to the frame columns. The failure modes and bearing capacities of joints with different structures were compared. Secondly, the experimental structures were verified through numerical simulation, and a database was constructed based on experimental and finite element results. Finally, an improved particle swarm optimization algorithm was used to optimize GPR, and the IPSO-GPR algorithm was proposed to form a prediction method for the bearing capacity of light steel frame structures. The results show that the proposed bearing capacity prediction method can better reflect the stress characteristics of such specimens. Light steel frame Beam–column joint area Post-earthquake axial compression performance GPR Carrying capacity Full Text Additional Declarations No competing interests reported. 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. 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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-8811407","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":599191347,"identity":"41539cf2-0a81-4db2-8526-32a3df268e83","order_by":0,"name":"Ding Wei","email":"","orcid":"","institution":"Guizhou University of Engineering Science","correspondingAuthor":false,"prefix":"","firstName":"Ding","middleName":"","lastName":"Wei","suffix":""},{"id":599191350,"identity":"d872dae0-3070-46c0-9ef3-6f2a4686e4f7","order_by":1,"name":"Jia Suizi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIie3QMWrDMBSAYRlBvLwgukkEfIYHXgO+ikUhk4ccIUYgL3FnLz1ECZSODoZ0cemaIYNDwVMGly5N8VC5Wwc77laIfhDigT4kRIjN9g9j1ImrEDkwpnIzdyscJiJRCpvl3BPZLhxHsHzWN1mz8DGPcBwhe6kpYCFXefn+AV8Hwlxjz0/9wsmkfutIrNLNbHpXE7E+oZOW/YRymfgdUeTlkU7XBcF9hNTR/WTCpZ51RJOo/iHBJQKw1SLDhQ8kmlD4NLfwC4S7sflknHuc73xxv6qBl/Vymw6QoHCPVdhyCF7VsTm1B48ltw/VeYD8zrwHuj0fC0ztH87abDbb1fQNecFaK5GxSNIAAAAASUVORK5CYII=","orcid":"","institution":"China University of Geosciences (Beijing)","correspondingAuthor":true,"prefix":"","firstName":"Jia","middleName":"","lastName":"Suizi","suffix":""}],"badges":[],"createdAt":"2026-02-07 01:08:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8811407/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8811407/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109170282,"identity":"d80169c7-1870-4229-b625-9a6b497356c4","added_by":"auto","created_at":"2026-05-13 08:47:03","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1402183,"visible":true,"origin":"","legend":"","description":"","filename":"BearingCapacityPredictionofLightweightSteel.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8811407/v1_covered_e9c840b6-4dee-4190-8eb7-f9b560eddc17.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bearing Capacity Prediction of Lightweight Steel Double L-Joints Based on Experimental Investigation and an Improved Gaussian Process Regression Algorithm","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Light steel frame, Beam–column joint area, Post-earthquake axial compression performance, GPR, Carrying capacity","lastPublishedDoi":"10.21203/rs.3.rs-8811407/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8811407/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe vertical load-bearing capacity of earthquake-damaged prefabricated frame structures determines their ability to resist collapse during aftershocks. 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