A Multiscale Event-Centered Framework for Quantifying Dynamic Reorganization in Aerodynamic Systems

A Multiscale Event-Centered Framework for Quantifying Dynamic Reorganization in Aerodynamic Systems | 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 A Multiscale Event-Centered Framework for Quantifying Dynamic Reorganization in Aerodynamic Systems Francisco Javier Martínez Sánchez. This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8672654/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 Aerodynamic performance is commonly evaluated using steady or time-averaged metrics such as lift, drag, or spectral energy content. While effective for characterizing mean behavior, these quantities often fail to capture changes in the temporal organization of the underlying dynamics induced by controlled modifications, particularly in unsteady and nonstationary flow regimes. Here we introduce a data-driven approach to diagnose dynamic reorganization in aerodynamic systems based on a multiscale, event-centered analysis of extreme fluctuations. Using a publicly available experimental dataset of unsteady aerodynamic load measurements obtained under multiple controlled forcing configurations, we define a scalar Aerodynamic Reorganization Index (IRA) that integrates complementary information from extreme-event statistics, critical activity density, and multichannel synchrony across measurement stations. The proposed index enables direct configuration-to-baseline comparison, providing a quantitative measure of how strongly a given modification alters the internal temporal organization of the system dynamics. Unlike classical amplitude- or energy-based indicators, the IRA is sensitive to collective, multichannel, and structural temporal changes, revealing dynamical reorganization even when conventional metrics remain largely unchanged. By focusing on temporal organization, intermittency, and collective dynamics, this approach complements conventional aerodynamic analysis and provides a physics-oriented diagnostic for comparing unsteady aerodynamic configurations prior to detailed modeling, simulation, or experimental refinement. Biogeography Dynamic reorganization Aerodynamic Reorganization Index (IRA) unsteady aerodynamics multiscale analysis event-centered analysis extreme events temporal organization multichannel synchronization criticality density extreme-event statistics baseline-referenced comparison intermittency temporal clustering collective dynamics regime transitions early-warning signals complex dynamical systems model-free diagnostics aerodynamic loads flow control diagnostics experimental screening 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8672654","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580861464,"identity":"dbb6dd82-c11a-43ea-856f-37f1e74e177e","order_by":0,"name":"Francisco Javier Martínez Sánchez.","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0000-4206-0608","institution":"Independent Researcher.","correspondingAuthor":true,"prefix":"","firstName":"Francisco","middleName":"Javier Martínez","lastName":"Sánchez.","suffix":""}],"badges":[],"createdAt":"2026-01-22 18:44:47","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8672654/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8672654/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101287983,"identity":"54dfbac9-f186-4c48-a1fc-8c00dd25ab0f","added_by":"auto","created_at":"2026-01-28 06:59:59","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1138984,"visible":true,"origin":"","legend":"","description":"","filename":"MartinezSanchezIRADynamicReorganizationAerodynamics.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8672654/v1_covered_0ffc4831-3275-4cae-9bb4-a533d9f2d892.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eA Multiscale Event-Centered Framework for Quantifying Dynamic\u003c/p\u003e\n\u003cp\u003eReorganization in Aerodynamic Systems\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","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":"Dynamic reorganization, Aerodynamic Reorganization Index (IRA), unsteady aerodynamics, multiscale analysis, event-centered analysis, extreme events, temporal organization, multichannel synchronization, criticality density, extreme-event statistics, baseline-referenced comparison, intermittency, temporal clustering, collective dynamics, regime transitions, early-warning signals, complex dynamical systems, model-free diagnostics, aerodynamic loads, flow control diagnostics, experimental screening","lastPublishedDoi":"10.21203/rs.3.rs-8672654/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8672654/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAerodynamic performance is commonly evaluated using steady or time-averaged metrics such as lift, drag, or spectral energy content. 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