Analytical prediction of yield strength for Ti-6Al-4V in laser powder bed fusion

Analytical prediction of yield strength for Ti-6Al-4V in laser powder bed fusion | 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 Analytical prediction of yield strength for Ti-6Al-4V in laser powder bed fusion Wei Huang, Hamid Garmestani, Steven Y. Liang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6779508/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 In additive manufacturing (AM), material properties are directly related to the evolution of microstructures affected by processing parameters. Compared to the traditional test-and-trial and finite element analysis (FEA) approaches, physics-based analytical simulation is more cost-efficient, resource-saving, and environmentally friendly for building the processing-structure-properties relationship to rapidly predict the microstructure evolution and material properties based on the input processing parameters. Yield strength is an important property that scholars and industries attach importance to. There has not been appropriate analytical work to model this property for laser powder bed fusion or AM. In this work, several theories, including the Hall-Petch equation, mechanical threshold stress (MTS), and grain size-modified MTS models, have been employed to predict the yield strength processed. Ti-6Al-4V, a popular alloy in industries such as aerospace and medical, is utilized as the sample material for validation. The prediction accuracy of various models has also been compared with the discussion. This work provides a capstone for the analytical simulation of yield strength for AM. Additive manufacturing Analytical modeling Laser powder bed fusion Yield strength Mechanical threshold stress Full Text Additional Declarations The authors declare no competing interests. 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. 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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-6779508","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":463843685,"identity":"f5e7a0d8-f203-4c1c-a41c-b530c81a258d","order_by":0,"name":"Wei Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYFACxgZmMM3eAyQOMMiAOTxEaeE5A9bCQ4QWBgaIFokcIrUYHG9uYC5ss8uTj3x78HHFGRsefokExgdv2/BoOXOwgXlmW3Kx4e28ZMMzN9J4JGckMBvOxaPF7EZiAzNvG3Pixtk5ZpINHw7zGNxIYJPmxafl/kOQlvrEjTPPmP9s+PCfx/5GAvtvvFpuMIK0HE6cL8Fjxthw4wCPgUQCGzM+LfZngA7jOXc8cQNPXrJkw5lkHokzD5sl55zDrUWy/fgDZp6y6sT57WcPfmw4ZifH35588MObMtxagID9B4g0OADjCyQ24FUPB/JwdfwHcKsaBaNgFIyCEQkATvpVeRkiUwMAAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Wei","middleName":"","lastName":"Huang","suffix":""},{"id":463843686,"identity":"f4f6aa78-d732-4714-9894-69280ee22eea","order_by":1,"name":"Hamid Garmestani","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hamid","middleName":"","lastName":"Garmestani","suffix":""},{"id":463843687,"identity":"267173ec-4219-4360-8550-53ad2c12b386","order_by":2,"name":"Steven Y. 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