Predicting the behavior of oxygen transfer processes induced by bubble plumes in water tanks using machine learning and higher order kinetics

Predicting the behavior of oxygen transfer processes induced by bubble plumes in water tanks using machine learning and higher order kinetics | 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 Predicting the behavior of oxygen transfer processes induced by bubble plumes in water tanks using machine learning and higher order kinetics Levy Felipe Santiago Saldanha, Francisco Judivan Celestino de Sousa, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6559592/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 The process of oxygen transfer to water has several applications in engineering and is referred to in the literature as a first-order kinetics. Its complexity in artificial aeration, however, introduces challenges to its evaluation. From this, several studies have proposed sophistications to this approach. This study explores a machine learning approach to predict the behavior of oxygen transfer by air injection in water tanks by predicting the reaeration coefficient considering higher-order kinetics. Eight machine learning models were studied considering coefficients with orders from 1 to 4 as output variables. The coefficients fitted to higher-orders resulted in the most promising models, with emphasis on order 2, which is justified by the complex mechanism composed of four main gas transfer processes that occur simultaneously. For this order, the tree-based models obtained the best metrics, and an analysis of feature importance was made for a better understanding of the interaction of the variables. Oxygen transfer. Bubble plumes. Reaeration coefficient. Higher-order kinetics. Machine learning. Full Text 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-6559592","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452022079,"identity":"ace93c5e-a5fe-4a94-b9cd-76f334f38c9d","order_by":0,"name":"Levy Felipe Santiago Saldanha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBACPigtw3CAgY2BoQLIAIIPDEAuLsAGpXkgWs4AGQwMjDOI18LYRowW9h4zCYY/djx8x88ee/Bznh2PwQEew4YfDHfycWrhOWMmwdiWzCN5Ji/dsHdbMlhLYw/DM8sGXFok0tIkGBuYgSpzzCR4t4EYPOaPGRgOG+C0Rf5ZGtBh9TwG59+YSf6dUw+2pRmvFgnmYxIMbId5DG7kmEnzNhwmQgtP8mGLxLbjPJI33phJyxwDMg6zFTb2GDzDqYWf/WDjjQ9/quX4zueYSb6pATKON29s+FFxB6cWIGCRSEDhM4MIfBqASj7glR4Fo2AUjIJRAACoaVBIVcZrIQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0002-1537-3830","institution":"Federal University of Ceara: Universidade Federal do Ceara","correspondingAuthor":true,"prefix":"","firstName":"Levy","middleName":"Felipe Santiago","lastName":"Saldanha","suffix":""},{"id":452022080,"identity":"9191c0e6-2428-4ebd-baab-e587195eb830","order_by":1,"name":"Francisco Judivan Celestino de Sousa","email":"","orcid":"","institution":"Federal University of Ceara: Universidade Federal do Ceara","correspondingAuthor":false,"prefix":"","firstName":"Francisco","middleName":"Judivan Celestino","lastName":"de Sousa","suffix":""},{"id":452022081,"identity":"6b431bcd-bb40-45cb-8a1c-665d1403f31f","order_by":2,"name":"Paulo Roberto Lacerda Tavares","email":"","orcid":"","institution":"Federal University of Cariri: Universidade Federal do Cariri","correspondingAuthor":false,"prefix":"","firstName":"Paulo","middleName":"Roberto Lacerda","lastName":"Tavares","suffix":""},{"id":452022082,"identity":"cf7ffcb4-220e-4a33-b548-3134ba34c9ee","order_by":3,"name":"Iran Eduardo Lima Neto","email":"","orcid":"https://orcid.org/0000-0001-8612-5848","institution":"Federal University of Ceara: Universidade Federal do Ceara","correspondingAuthor":false,"prefix":"","firstName":"Iran","middleName":"Eduardo Lima","lastName":"Neto","suffix":""}],"badges":[],"createdAt":"2025-04-29 21:58:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6559592/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6559592/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84350395,"identity":"3c6cba1d-b0f7-485b-b181-9df142b71e71","added_by":"auto","created_at":"2025-06-10 23:40:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1812452,"visible":true,"origin":"","legend":"","description":"","filename":"ArtigoMLbubleplumesBJCE.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6559592/v1_covered_63f2f581-8577-4d15-8dca-b0e893e5c1d2.pdf"}],"financialInterests":"","formattedTitle":"Predicting the behavior of oxygen transfer processes induced by bubble plumes in water tanks using machine learning and higher order kinetics","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Oxygen transfer. 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