A PCM based rigid-flexible coupled dynamic modeling approach for post-derailment response analysis of URT vehicles | 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 A PCM based rigid-flexible coupled dynamic modeling approach for post-derailment response analysis of URT vehicles Weicheng Li, Jiahe Gao, Jingsong Xie, Guifa Huang, Yulong Wu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8472112/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract As unmanned driving technology advances, the autonomous safety of urban rail transit (URT) vehicles has been recognized as a paramount concern. As the final line of defense for the safety of autonomous operations, research into post-derailment behavior is deemed critical for the assessment of operational safety and the prevention of accident escalation. However, existing derailment monitoring and post-derailment alarm systems, which rely on axle box acceleration (ABA) signals, lack clear standards and evaluation metrics for identifying and assessing post-derailment impact responses. To address this issue, a rigid-flexible modeling approach based on the polygon contact model (PCM) is proposed to accurately simulate post-derailment dynamic behavior and impact responses. A multi-rigid-body vehicle-track model is established using Type A URT vehicle parameters, with flexible wheelsets and rails replacing rigid components. Hertz and PCM contacts are applied to pre- and post-derailment areas respectively, developing a rigid-flexible coupled derailment dynamics model (RFCDDM). The feasibility and accuracy of RFCDDM are verified through comparisons with monitored ABA data and derailment tests. Further, the verified model is used to reproduce post-derailment scenarios under varied speed-load combinations, revealing impact amplitude variation laws. The results indicate that increased speed shifts wheelset lateral displacement-induced impact locations from fasteners to sleepers or track beds; the first impact response presents a “rise-fall-rise” trend, while continuous impacts show attenuation. These findings support the optimization on optimizing safety evaluation systems for health monitoring in the operation of URT vehicles. Urban rail transit vehicle Dynamics Post-derailment Rigid-flexible coupling Polygonal Contact Model (PCM) Passive safety Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 28 Mar, 2026 Reviews received at journal 18 Mar, 2026 Reviews received at journal 24 Feb, 2026 Reviews received at journal 16 Feb, 2026 Reviewers agreed at journal 28 Jan, 2026 Reviewers agreed at journal 28 Jan, 2026 Reviewers agreed at journal 27 Jan, 2026 Reviewers invited by journal 26 Jan, 2026 Editor assigned by journal 02 Jan, 2026 Submission checks completed at journal 30 Dec, 2025 First submitted to journal 29 Dec, 2025 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. 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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-8472112","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582080194,"identity":"fb961297-97d2-4718-8996-f111cf81cacb","order_by":0,"name":"Weicheng Li","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Weicheng","middleName":"","lastName":"Li","suffix":""},{"id":582080199,"identity":"48ef2531-e00c-4360-8ece-a211608a837e","order_by":1,"name":"Jiahe Gao","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Jiahe","middleName":"","lastName":"Gao","suffix":""},{"id":582080200,"identity":"a57928a7-4395-4246-b241-7edd358be31c","order_by":2,"name":"Jingsong Xie","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Jingsong","middleName":"","lastName":"Xie","suffix":""},{"id":582080201,"identity":"d4c92763-3415-4a4f-b719-2f4ef3ff386e","order_by":3,"name":"Guifa Huang","email":"","orcid":"","institution":"Beijing Tangzhi Science and Technology Development Co. 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