ANN-Based Ground Motion and Physics-Based Broadband Models for Vertical Spectra

ANN-Based Ground Motion and Physics-Based Broadband Models for Vertical Spectra | 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 ANN-Based Ground Motion and Physics-Based Broadband Models for Vertical Spectra Varun Sharma, Harsh Kumar Arya, Mahesreddy Gade, J Dhanya This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4287445/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Feb, 2025 Read the published version in Pure and Applied Geophysics → Version 1 posted 9 You are reading this latest preprint version Abstract Vertical ground motion plays a crucial role in the design of critical structures, with recorded vertical ground motions often surpassing their horizontal counterparts in the near-field. This study proposes a new simplified Ground Motion Model (GMM) for vertical spectra by combining comprehensive datasets from the NESS and NGA-West2 databases. The proposed Artificial Neural Network (ANN) architecture-based model requires only 288 unknowns to predict spectral accelerations ($Sa$) at 33 distinct periods ranging from 0 to 4 seconds. Notably, this model inherently captures known physical phenomena with reduced variability using a minimum number of unknowns compared to the GMMs existing literature, thus offering a valuable addition to current hazard estimation frameworks. Furthermore, recognizing the necessity for physics-based simulations in vertical ground motion analysis, we introduce a novel physics-based broadband model for vertical spectra using ANN methodology. The proposed broadband model exhibits better robustness due to the comprehensiveness of the dataset utilized and the inclusion of source path and site characteristics at the input layer. Additionally, the model effectively captures the physical trends with minimal deviation. Further, a comparison of the model's output with physics-based simulations for the 2008 Mw 6.9 Iwate earthquake and recorded data showcase its ability to accurately capture the non-ergodic nature of ground motion. The proposed models serve as essential tools for physics-based broadband simulations and hazard assessments in active shallow crustal regions. Vertical ground motions Ground motion model (GMM) Artificial Neural Network (ANN) Broadband spectra Physics-based simulation Non-ergodic nature of ground motions. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Feb, 2025 Read the published version in Pure and Applied Geophysics → Version 1 posted Editorial decision: Revision requested 31 Jul, 2024 Reviews received at journal 30 Jul, 2024 Reviews received at journal 27 Jun, 2024 Reviewers agreed at journal 04 Jun, 2024 Reviewers agreed at journal 31 May, 2024 Reviewers invited by journal 26 May, 2024 Editor assigned by journal 20 Apr, 2024 Submission checks completed at journal 20 Apr, 2024 First submitted to journal 18 Apr, 2024 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-4287445","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":293450901,"identity":"c82d9ba8-0377-43c2-959a-c88e38185348","order_by":0,"name":"Varun Sharma","email":"","orcid":"","institution":"Indian Institute of Technology Mandi","correspondingAuthor":false,"prefix":"","firstName":"Varun","middleName":"","lastName":"Sharma","suffix":""},{"id":293450903,"identity":"ef2b97af-6d19-42a3-94a9-ce9faa702e78","order_by":1,"name":"Harsh Kumar Arya","email":"","orcid":"","institution":"Indian Institute of Technology Mandi","correspondingAuthor":false,"prefix":"","firstName":"Harsh","middleName":"Kumar","lastName":"Arya","suffix":""},{"id":293450905,"identity":"d00293d5-9022-4705-bb61-d7c86610cbec","order_by":2,"name":"Mahesreddy Gade","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYFACHgYGxgYgfSCB8UGCAVjI4ACIZCNCC7NBgoEBaVrYJICqwVrwOku3/ezBhz933JPjO55jVvGg4E80/+zmjQcYauwY+KQbsGoxO5OXbMx7pthY8swbsxtAh+XOuHOs4ADDsWQGNpkD2LUcyDGTZmxLSNxwIweipeFGDtAvbEAkkYBdy/k35j9/tiXUg7QUgLTMB2v5h0cLUCUDb1tCggGIAdKyAaSFsQ2fljfG0kAthjPPPCuWSDAwzt14I63gQGJfMg9uh+UYfgQ6TJ7vePLGjz/+yOXOu5G8+cOHb3Zy8jOwa0ECHEjRkQCOL4KA/QERikbBKBgFo2AkAgCT82f0dkpwlQAAAABJRU5ErkJggg==","orcid":"","institution":"Indian Institute of Technology Mandi","correspondingAuthor":true,"prefix":"","firstName":"Mahesreddy","middleName":"","lastName":"Gade","suffix":""},{"id":293450908,"identity":"b09cc382-ea45-4b03-9dc9-9c6bafa5cbc7","order_by":3,"name":"J Dhanya","email":"","orcid":"","institution":"Indian Institute of Technology Mandi","correspondingAuthor":false,"prefix":"","firstName":"J","middleName":"","lastName":"Dhanya","suffix":""}],"badges":[],"createdAt":"2024-04-18 11:32:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4287445/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4287445/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00024-025-03660-y","type":"published","date":"2025-02-01T15:57:30+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":75351799,"identity":"6c6cd10a-ecb2-45b2-af6d-42236b4c6596","added_by":"auto","created_at":"2025-02-03 16:12:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6638170,"visible":true,"origin":"","legend":"","description":"","filename":"PAGPsubmission.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4287445/v1_covered_4d7ce460-126d-4f00-91ca-0e2271e5894c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"ANN-Based Ground Motion and Physics-Based Broadband Models for Vertical Spectra","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":"pure-and-applied-geophysics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"paag","sideBox":"Learn more about [Pure and Applied Geophysics](https://www.springer.com/journal/24)","snPcode":"24","submissionUrl":"https://submission.nature.com/new-submission/24/3","title":"Pure and Applied Geophysics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Vertical ground motions, Ground motion model (GMM), Artificial Neural Network (ANN), Broadband spectra, Physics-based simulation, Non-ergodic nature of ground motions.","lastPublishedDoi":"10.21203/rs.3.rs-4287445/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4287445/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Vertical ground motion plays a crucial role in the design of critical structures, with recorded vertical ground motions often surpassing their horizontal counterparts in the near-field. 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