Multi-objective optimization of forging surface structure parameters of radial forging die with cycloidal

Multi-objective optimization of forging surface structure parameters of radial forging die with cycloidal | 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 Multi-objective optimization of forging surface structure parameters of radial forging die with cycloidal Junshi Wang, Zhaohui Wang, Wenxia Xu, Zun Du, Hongxia Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2578533/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Nov, 2023 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted 4 You are reading this latest preprint version Abstract To improve the strain homogeneity and damage homogeneity of radial forging hollow shaft. Proposed radial forging die with a cycloid as a generatrix entrance surface. The effects of the structural parameters of the die forging surface, such as the radius of cycloid base circle (R), the length of sizing zone (L) and the radius of sizing zone (r) on the strain homogeneity and damage homogeneity of the machined shaft were investigated. Numerical simulations were performed according to the orthogonal design L 25 , and an artificial neural network approach was used to develop a mathematical prediction model and apply it to the optimization process of the genetic algorithm. The results show that the optimized structural parameters of the compromise solution are R = 68.27mm, L = 49.36mm, r = 11.01mm, ε σ and C σ are 0.2113 and 0.02562, respectively. Compared with the original structural scheme, ε σ is reduced by 21.83% and C σ is reduced by 31.58%, which indicates that the plastic deformation is more uniform and the machining damage is less during the hollow shaft forging process. Radial forging die Forging surface structure parameters Multi-objective optimization Strain homogeneity Damage homogeneity. Full Text Cite Share Download PDF Status: Published Journal Publication published 18 Nov, 2023 Read the published version in The International Journal of Advanced Manufacturing Technology → Version 1 posted Editorial decision: Major Revisions Needed 11 Jun, 2023 Reviewers agreed at journal 16 Feb, 2023 Editor assigned by journal 14 Feb, 2023 First submitted to journal 13 Feb, 2023 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-2578533","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":176508710,"identity":"179f2580-1283-478a-a0c8-194c17e22b3d","order_by":0,"name":"Junshi 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Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Radial forging die, Forging surface structure parameters, Multi-objective optimization, Strain homogeneity, Damage homogeneity.","lastPublishedDoi":"10.21203/rs.3.rs-2578533/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2578533/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo improve the strain homogeneity and damage homogeneity of radial forging hollow shaft. Proposed radial forging die with a cycloid as a generatrix entrance surface. The effects of the structural parameters of the die forging surface, such as the radius of cycloid base circle (R), the length of sizing zone (L) and the radius of sizing zone (r) on the strain homogeneity and damage homogeneity of the machined shaft were investigated. Numerical simulations were performed according to the orthogonal design L\u003csub\u003e25\u003c/sub\u003e, and an artificial neural network approach was used to develop a mathematical prediction model and apply it to the optimization process of the genetic algorithm. The results show that the optimized structural parameters of the compromise solution are R = 68.27mm, L = 49.36mm, r = 11.01mm, ε\u003csub\u003eσ\u003c/sub\u003e and C\u003csub\u003eσ\u003c/sub\u003e are 0.2113 and 0.02562, respectively. Compared with the original structural scheme, ε\u003csub\u003eσ\u003c/sub\u003e is reduced by 21.83% and C\u003csub\u003eσ\u003c/sub\u003e is reduced by 31.58%, which indicates that the plastic deformation is more uniform and the machining damage is less during the hollow shaft forging process.\u003c/p\u003e","manuscriptTitle":"Multi-objective optimization of forging surface structure parameters of radial forging die with cycloidal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-02-17 22:31:29","doi":"10.21203/rs.3.rs-2578533/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revisions Needed","date":"2023-06-11T06:41:40+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2023-02-16T05:20:07+00:00","index":0,"fulltext":""},{"type":"editorAssigned","content":"","date":"2023-02-15T03:59:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"The International Journal of Advanced Manufacturing Technology","date":"2023-02-14T04:31:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"the-international-journal-of-advanced-manufacturing-technology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jamt","sideBox":"Learn more about [The International Journal of Advanced Manufacturing Technology](https://www.springer.com/journal/170)","snPcode":"170","submissionUrl":"https://submission.nature.com/new-submission/170/3","title":"The International Journal of Advanced Manufacturing Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d7da06c5-1c7b-4170-8fdc-bd9b3c41e927","owner":[],"postedDate":"February 17th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-11-20T15:08:01+00:00","versionOfRecord":{"articleIdentity":"rs-2578533","link":"https://doi.org/10.1007/s00170-023-12629-x","journal":{"identity":"the-international-journal-of-advanced-manufacturing-technology","isVorOnly":false,"title":"The International Journal of Advanced Manufacturing Technology"},"publishedOn":"2023-11-18 15:01:28","publishedOnDateReadable":"November 18th, 2023"},"versionCreatedAt":"2023-02-17 22:31:29","video":"","vorDoi":"10.1007/s00170-023-12629-x","vorDoiUrl":"https://doi.org/10.1007/s00170-023-12629-x","workflowStages":[]},"version":"v1","identity":"rs-2578533","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2578533","identity":"rs-2578533","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}