Ghost particle suppression multiplicative algebraic reconstruction technique for tomographic PIV

Ghost particle suppression multiplicative algebraic reconstruction technique for tomographic PIV | 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 Ghost particle suppression multiplicative algebraic reconstruction technique for tomographic PIV Peng Lei, Hua Yang, Zhouping Yin, Feng Shan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4229125/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Jan, 2025 Read the published version in Experiments in Fluids → Version 1 posted 9 You are reading this latest preprint version Abstract The exponential distribution law of the intensity of tomographic particle image velocimetry (Tomo-PIV) reconstructed particles is validated via a probabilistic approach. Moreover, based on the distribution law of ghost particles and the self-similarity of particles, a new Tomo-PIV particle reconstruction method is proposed. In this method, ghost particles are treated as reconstruction noise. Furthermore, a combination of variational denoising methods and the inversediffusion equation with regularization constraint for ghost particles suppression. This method is called ghost particle suppression multiplicative algebraic reconstruction technique(GS-MART). The proposed algorithm is evaluated numerically on cylindrical wake simulation data, and the reconstruction quality, intensity distribution of true particles and ghost particles, and velocity calculation accuracy are analyzed under different particle densities. To verify the application effect of GS-MART, experiments were carried out in jet flows, and the results showed that the high-precision 3D particle reconstruction results of GS-MART significantly improved the velocity field estimation results. Particle reconstruction Tomo-PIV Ghost particle suppression Particle intensity distribution Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 23 Jan, 2025 Read the published version in Experiments in Fluids → Version 1 posted Editorial decision: Revision requested 15 Jun, 2024 Reviews received at journal 14 Jun, 2024 Reviewers agreed at journal 24 May, 2024 Reviews received at journal 13 May, 2024 Reviewers agreed at journal 23 Apr, 2024 Reviewers invited by journal 21 Apr, 2024 Editor assigned by journal 10 Apr, 2024 Submission checks completed at journal 10 Apr, 2024 First submitted to journal 06 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. 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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-4229125","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":289872494,"identity":"9587b229-537f-4fc7-8a13-6719ccee6dc0","order_by":0,"name":"Peng Lei","email":"","orcid":"","institution":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Lei","suffix":""},{"id":289872495,"identity":"3cd8cf79-8637-43ac-85af-849bb9d9b306","order_by":1,"name":"Hua Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYBACAygtB2UwE6/FGMhgbCBJS+IGorWYSyQ/k/i5ozZ9u0T68wcMFdaJDexnD+DVYjkjzUyy98zx3J0zcgwbGM6kJzbw5CXgd9iNBDMJ3rZjuRtu5DA2MLYdTmyQ4DEgoCX9m+TftmPpQMbDBsZ/RGnJMZPmbatJAFpn2MDYQIyWM2+KrWXbDhhuOPPGcEbCsXTjNp4cAlqOp2+8+batTh7IePDhQ421bD/7GfxagIBFgoHhMISZAMRshNQDAfMHBoY6ItSNglEwCkbBiAUA1AZK3b6IcKAAAAAASUVORK5CYII=","orcid":"","institution":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Hua","middleName":"","lastName":"Yang","suffix":""},{"id":289872496,"identity":"df0e2b6f-2b2a-4848-a6c1-a4c2c0f1fe3d","order_by":2,"name":"Zhouping Yin","email":"","orcid":"","institution":"School of Mechanical Science and Engineering, Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Zhouping","middleName":"","lastName":"Yin","suffix":""},{"id":289872497,"identity":"cc3e4d15-563d-4816-bf15-ca89f9e659dd","order_by":3,"name":"Feng Shan","email":"","orcid":"","institution":"School of Energy and Power Engineering, Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Shan","suffix":""}],"badges":[],"createdAt":"2024-04-07 01:59:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4229125/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4229125/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00348-024-03935-5","type":"published","date":"2025-01-23T15:57:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":74858591,"identity":"01c10b35-680a-4640-8780-2a7cd889cfe2","added_by":"auto","created_at":"2025-01-27 16:11:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2926178,"visible":true,"origin":"","legend":"","description":"","filename":"GSMART.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4229125/v1_covered_628e650c-64f4-4a90-9329-42b43bd7c241.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ghost particle suppression multiplicative algebraic reconstruction technique for tomographic PIV","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":"experiments-in-fluids","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"exif","sideBox":"Learn more about [Experiments in Fluids](http://link.springer.com/journal/348)","snPcode":"348","submissionUrl":"https://submission.nature.com/new-submission/348/3","title":"Experiments in Fluids","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Particle reconstruction, Tomo-PIV, Ghost particle suppression, Particle intensity distribution","lastPublishedDoi":"10.21203/rs.3.rs-4229125/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4229125/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The exponential distribution law of the intensity of tomographic particle image velocimetry (Tomo-PIV) reconstructed particles is validated via a probabilistic approach. 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