Integrated Stochastic Modeling and Neural Networks for Inverse Prediction of Elastic Modulus in Beams

Integrated Stochastic Modeling and Neural Networks for Inverse Prediction of Elastic Modulus in Beams | 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 Integrated Stochastic Modeling and Neural Networks for Inverse Prediction of Elastic Modulus in Beams rakesh kumar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5799356/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract In this work we have obtained elastic modulus from the eigen frequencies of a cantilever beam. The elastic modulus of the beam has random elastic modulus haing exponential covariance function. We have used Monte Carlo simulations with cholesky decomposition to obtain the elastic modulus and eigen frequency data. The data driven non intrusive polynomial chaos is used to obtain eigen elastic modulus from the eigen frequencies. The difference between the elastic modulus data obtained from MCS and NiPCE are used to train a neural network. For new prediction the elastic modulus data from PCE and the difference from neural network are added. The final results shows remarkable resemble with actual data or MCs data. Also the computational time of our proposed method is significantly lower than mcs time as the neural network once trained need smaller time to give the output. Eigen frequencies Polynomial Chaos Monte Carlo Simulation Rotating cantilever bean Vibration Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Mar, 2025 Reviews received at journal 03 Mar, 2025 Reviews received at journal 11 Feb, 2025 Reviewers agreed at journal 03 Feb, 2025 Reviewers agreed at journal 01 Feb, 2025 Reviewers invited by journal 01 Feb, 2025 Editor assigned by journal 11 Jan, 2025 Submission checks completed at journal 10 Jan, 2025 First submitted to journal 09 Jan, 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-5799356","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":400807372,"identity":"c2acf04a-38f9-4a28-8276-896bd62a8f8f","order_by":0,"name":"rakesh kumar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACCShlZ3+8seEAAw+Iw9hAjBaLZIYzBxsOHCBBSwVjw40EBoYDxDhMckZ24ucKBglmxpmPGw9/kGGQ529gbnuAT4u0RO5myTMMEnzM0olghxnOOMDYboBPi5xE7gbJBqAtbFAtjBsYGNskCGjZ/BOohbFHEuJ9e4JagA7bBrKFcYYEI1hLIkEtkj1vt1k2GEgkG/AAHXaGRyJ5xmECWiSO526+2VBRZ2fAfvzxh8oeG9v+9vZneLVAACyEGHuAipkJq0cGP0hTPgpGwSgYBSMDAADE3EYIuPIkVgAAAABJRU5ErkJggg==","orcid":"","institution":"IIT Jodhpur","correspondingAuthor":true,"prefix":"","firstName":"rakesh","middleName":"","lastName":"kumar","suffix":""}],"badges":[],"createdAt":"2025-01-09 22:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5799356/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5799356/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73699096,"identity":"5cee1275-85f1-48b8-b752-9a15c18fa1db","added_by":"auto","created_at":"2025-01-13 16:52:34","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":935359,"visible":true,"origin":"","legend":"","description":"","filename":"inverseelasticmodulus.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5799356/v1_covered_99a28e50-1adf-4b7d-80a3-4390e32f7909.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated Stochastic Modeling and Neural Networks for Inverse Prediction of Elastic Modulus in Beams","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-applied-and-computational-mathematics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [International Journal of Applied and Computational Mathematics](https://link.springer.com/journal/40819)","snPcode":"40819","submissionUrl":"https://submission.nature.com/new-submission/40819/3","title":"International Journal of Applied and Computational Mathematics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Eigen frequencies, Polynomial Chaos, Monte Carlo Simulation, Rotating cantilever bean, Vibration","lastPublishedDoi":"10.21203/rs.3.rs-5799356/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5799356/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In this work we have obtained elastic modulus from the eigen frequencies of a cantilever beam. 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