Experimentally Calibrated Nonlinear Hinge Models for H-Shaped Beams, HSS Columns, and H-Shaped Braces in Steel Frames

Experimentally Calibrated Nonlinear Hinge Models for H-Shaped Beams, HSS Columns, and H-Shaped Braces in Steel Frames | 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 Experimentally Calibrated Nonlinear Hinge Models for H-Shaped Beams, HSS Columns, and H-Shaped Braces in Steel Frames Mojtaba Fathisepahvand, Min-Lang Lin, Chao-Hsun Huang, Tsung-Chih Chiou, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7843466/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 This study develops and validates a suite of computationally efficient nonlinear hinge models to enable accurate performance-based seismic assessment of steel moment-resisting frames (MRFs) and concentrically braced frames (CBFs). Derived from a comprehensive regression analysis of 66 cyclic tests on beams, columns, and braces, which include modern high-strength steels such as SM570 and SN490B, the proposed formulations comprise three specialized models: a flexural model for H-shaped beams, an axial model for H-shaped braces, and a flexural-axial interaction model for HSS columns. These models explicitly capture critical inelastic behaviors such as local buckling, asymmetric hysteresis, and strength degradation. Rigorous component-level validation was performed by benchmarking the proposed models against experimental results and code provisions, demonstrating substantially improved accuracy in predicting deformation capacity, strength, and asymmetric hysteretic response. The practical efficacy of the models was further demonestrated through system-level case studies of a 15-story MRF and a two-story CBF, analyzed within an ASCE 41 − 23 compliant framework integrating nonlinear static pushover analysis (NSPA) and the capacity spectrum method (CSM). The results demonstrate the proposed models' superior predictive accuracy, successfully quantifying global overstrength and identifying localized weak-story mechanisms that were not captured by the standard approach, providing engineers with a robust tool for performance-based seismic evaluation. Seismic performance steel structures nonlinear hinge models experimental calibration nonlinear static pushover analysis (NSPA) Full Text 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-7843466","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":540658684,"identity":"5f3e5604-cdc9-408b-9ae2-9403787a377b","order_by":0,"name":"Mojtaba 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