PE-WFormer: Physical enhanced sparse data-driven wind field reconstruction for bluff body

PE-WFormer: Physical enhanced sparse data-driven wind field reconstruction for bluff body | 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 PE-WFormer: Physical enhanced sparse data-driven wind field reconstruction for bluff body Lei Zhou, Yong Xia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8763040/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 Wind field distribution around bluff bodies is a critical factor in structural wind resistance design and aerodynamic performance evaluation. Traditional computational fluid dynamics (CFD) methods face challenges such as high computational cost, long test cycles, and difficulty in capturing full-field dynamic characteristics. Physics-Informed Neural Networks (PINNs) have emerged as a promising tool for getting fluid dynamics via sparse data, but conventional MLP-based PINNs neglect temporal dependencies in unsteady bluff body flow, leading to inaccurate full-field reconstruction from sparse data. In this paper, we propose an improved data-driven framework tailored for bluff body flow reconstruction via sparse data, leveraging Transformer’s strong capability in capturing spatiotemporal dependencies to address the limitations of traditional PINNs. We validate the proposed framework using CFD data of a typical bluff body. Experimental results demonstrate that the proposed framework outperforms conventional PINNs, in terms of reconstruction accuracy. This work provides a high-efficiency, high-accuracy data-driven method for wind field reconstruction of bluff body, offering practical support for structural wind resistance design and aerodynamic optimization. Civil Engineering PE-WFormer Bluff body flow Wind field reconstruction Sparse data Spatiotemporal dependency 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. 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-8763040","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":584190998,"identity":"fea46db8-44f0-45b2-8e87-7966f03335a3","order_by":0,"name":"Lei Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBACPgYeMC2HIsrMcAC3FjaoFmMo3wCsgSgtiQ3Ea+E/e/AxT83h9P723mMPPtT8YTA4f/4Ac8EZfLacSzbmOXY4d8aZc+mGM44ZMBjcSGZgnnEDjxbGHjNpHrbDuRskcsykeRtAWoAO4/mARwszD1DLv8PpBiAtf0Fazh8moIUNqIW37XACWAsjSMsBoMN48DmMh8fYcG4f0BtnzphJ9hwz5pG8kWxwmAeP9/n5zxg+ePPNWp6/vcdM4keNnBzf+YMPH/Mcw60FA4Cj6QAJGkbBKBgFo2AUYAEAXN5G0QzPbpYAAAAASUVORK5CYII=","orcid":"","institution":"Hong Kong PolyU","correspondingAuthor":true,"prefix":"","firstName":"Lei","middleName":"","lastName":"Zhou","suffix":""},{"id":584190999,"identity":"3b33526e-daea-4ad1-8bca-6a198f04687b","order_by":1,"name":"Yong Xia","email":"","orcid":"","institution":"Hong Kong PolyU","correspondingAuthor":false,"prefix":"","firstName":"Yong","middleName":"","lastName":"Xia","suffix":""}],"badges":[],"createdAt":"2026-02-02 09:28:11","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-8763040/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8763040/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101881227,"identity":"f9099da5-4a75-460e-87cf-89e7fabf9d46","added_by":"auto","created_at":"2026-02-04 15:10:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":472001,"visible":true,"origin":"","legend":"","description":"","filename":"PEWFormor.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8763040/v1_covered_c4ce636b-a407-4beb-ac63-f554648f45e6.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePE-WFormer: Physical enhanced sparse data-driven wind field reconstruction for bluff body\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Hong Kong Polytechnic University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PE-WFormer, Bluff body flow, Wind field reconstruction, Sparse data, Spatiotemporal dependency","lastPublishedDoi":"10.21203/rs.3.rs-8763040/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8763040/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWind field distribution around bluff bodies is a critical factor in structural wind resistance design and aerodynamic performance evaluation. 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