Pre-research on enhanced heat transfer method for special vehicles at high altitude based on machine learning

Pre-research on enhanced heat transfer method for special vehicles at high altitude based on machine learning | 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 Pre-research on enhanced heat transfer method for special vehicles at high altitude based on machine learning Chunming Li, Xiaoxia Sun, Hongyang Gao, Yu Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1776007/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Apr, 2023 Read the published version in Chinese Journal of Mechanical Engineering → Version 1 posted 6 You are reading this latest preprint version Abstract The performance of the thermal management system has a great influence on the stability of the special purpose vehicles, and it is of great significance to enhance heat transfer of the radiator. Common research methods for radiators include fluid mechanics numerical simulation and experimental measurements, both of which are time-consuming and expensive. Applying the surrogate model to the analysis of flow and heat transfer in louver fin can effectively reduce the computational cost and obtain more data. A simplified louver fin heat transfer unit is established, and computational fluid dynamics (CFD) simulations is used to obtain the flow and heat transfer characteristics of this geometry structure. A three-factor and six-level orthogonal design is carried out with three structural parameters, the angle θ, the length a and the spacing Lp of the louver fins. The results of the orthogonal design are subjected to range analysis, and the effects of the three parameters θ, a and Lp on the j, f and JF factors are obtained. On this basis, a proxy model of the heat transfer performance for louver fins was established based on the artificial neural network algorithm, and the model was trained with the data obtained by the orthogonal design, and finally the fin structure with the largest JF factor was found. Compared with the original model, the optimized model improves the heat transfer factor j by 2.87%, the friction factor f decreases by 30.4% and the comprehensive factor JF increases by 15.7%. Louver fins Numerical simulation Machine learning Comprehensive performance Full Text Cite Share Download PDF Status: Published Journal Publication published 06 Apr, 2023 Read the published version in Chinese Journal of Mechanical Engineering → Version 1 posted Editorial decision: Minor revision 10 Jan, 2023 Reviewers agreed at journal 28 Sep, 2022 Reviewers invited by journal 25 Jul, 2022 Editor invited by journal 12 Jul, 2022 Editor assigned by journal 25 Jun, 2022 First submitted to journal 24 Jun, 2022 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-1776007","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":123665546,"identity":"20ec63b9-a880-459b-9b74-3e91e11c712b","order_by":0,"name":"Chunming Li","email":"","orcid":"","institution":"China North Vehicle Research Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chunming","middleName":"","lastName":"Li","suffix":""},{"id":123665547,"identity":"1aba5620-1c81-4665-bf3f-de915956732f","order_by":1,"name":"Xiaoxia Sun","email":"","orcid":"","institution":"China North Vehicle Research Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaoxia","middleName":"","lastName":"Sun","suffix":""},{"id":123665548,"identity":"0f79e21d-c522-4c63-bf88-5df53cd71664","order_by":2,"name":"Hongyang Gao","email":"","orcid":"","institution":"Zhejiang University City College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hongyang","middleName":"","lastName":"Gao","suffix":""},{"id":123665549,"identity":"80d1c183-e4ce-4f95-b342-1d0d91659641","order_by":3,"name":"Yu Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYDACCWTOB2yCeLUwziBZCzMPMVrkZzc/e/i17TCDvPsZM2mbP4fl+RuYD97mYbDLw6WFcc4xc2NZoBbDM2lp0jk8hw1nHGBLtuZhSC7GpYVZIsFMWhKkZQbzMekcicMJBgw8ZtI8DAcSG3BoYZNI/wbVwtgmbWEA0sL/Da8WHokcM8mPIL9IAG1hSADbwoZXi4RETpk0w7l0BgOetGTLngPphjMOsxlbzjFIxqlFfkb6NskfZdYM8u1nDG/8+GMtz9/e/PDGmwo7nFrAQcDLxlC/4QADCyQ6mEGEAR71QMD44w/QugYG5g/41Y2CUTAKRsFIBQDKhkynK3fyvAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-5559-887X","institution":"Zhejiang University City College","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2022-06-20 09:47:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1776007/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1776007/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s10033-023-00873-x","type":"published","date":"2023-04-06T20:22:20+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":24526084,"identity":"3fa54e74-aa9b-45c6-b985-4f150f2f5aca","added_by":"auto","created_at":"2022-07-29 18:23:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1072500,"visible":true,"origin":"","legend":"","description":"","filename":"Cjmenetlouverfinv1.2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1776007/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"Pre-research on enhanced heat transfer method for special vehicles at high altitude based on machine learning","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-1776007/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"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":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"chinese-journal-of-mechanical-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"chme","sideBox":"Learn more about [Chinese Journal of Mechanical Engineering](https://cjme.springeropen.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/chme/default.aspx","title":"Chinese Journal of Mechanical Engineering","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Louver fins , Numerical simulation , Machine learning , Comprehensive performance","lastPublishedDoi":"10.21203/rs.3.rs-1776007/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1776007/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The performance of the thermal management system has a great influence on the stability of the special purpose vehicles, and it is of great significance to enhance heat transfer of the radiator. Common research methods for radiators include fluid mechanics numerical simulation and experimental measurements, both of which are time-consuming and expensive. Applying the surrogate model to the analysis of flow and heat transfer in louver fin can effectively reduce the computational cost and obtain more data. A simplified louver fin heat transfer unit is established, and computational fluid dynamics (CFD) simulations is used to obtain the flow and heat transfer characteristics of this geometry structure. A three-factor and six-level orthogonal design is carried out with three structural parameters, the angle θ, the length a and the spacing Lp of the louver fins. The results of the orthogonal design are subjected to range analysis, and the effects of the three parameters θ, a and Lp on the j, f and JF factors are obtained. On this basis, a proxy model of the heat transfer performance for louver fins was established based on the artificial neural network algorithm, and the model was trained with the data obtained by the orthogonal design, and finally the fin structure with the largest JF factor was found. Compared with the original model, the optimized model improves the heat transfer factor j by 2.87%, the friction factor f decreases by 30.4% and the comprehensive factor JF increases by 15.7%.","manuscriptTitle":"Pre-research on enhanced heat transfer method for special vehicles at high altitude based on machine learning","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-07-29 18:23:47","doi":"10.21203/rs.3.rs-1776007/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2023-01-10T20:38:09+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2022-09-28T09:48:06+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-07-25T08:27:43+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Chinese Journal of Mechanical Engineering","date":"2022-07-12T08:54:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-06-25T11:39:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Chinese Journal of Mechanical Engineering","date":"2022-06-24T10:27:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"chinese-journal-of-mechanical-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"chme","sideBox":"Learn more about [Chinese Journal of Mechanical Engineering](https://cjme.springeropen.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/chme/default.aspx","title":"Chinese Journal of Mechanical Engineering","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e4af50a9-d372-40a7-9350-fa944441566f","owner":[],"postedDate":"July 29th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T20:29:12+00:00","versionOfRecord":{"articleIdentity":"rs-1776007","link":"https://doi.org/10.1186/s10033-023-00873-x","journal":{"identity":"chinese-journal-of-mechanical-engineering","isVorOnly":false,"title":"Chinese Journal of Mechanical Engineering"},"publishedOn":"2023-04-06 20:22:20","publishedOnDateReadable":"April 6th, 2023"},"versionCreatedAt":"2022-07-29 18:23:47","video":"","vorDoi":"10.1186/s10033-023-00873-x","vorDoiUrl":"https://doi.org/10.1186/s10033-023-00873-x","workflowStages":[]},"version":"v1","identity":"rs-1776007","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1776007","identity":"rs-1776007","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}