Comparative Study of Atmospheric and Submerged AWJM Performance on Nimonic-90 Superalloy: Depth of Penetration Analysis and Hybrid Cohort Intelligence Modeling

Comparative Study of Atmospheric and Submerged AWJM Performance on Nimonic-90 Superalloy: Depth of Penetration Analysis and Hybrid Cohort Intelligence Modeling | 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 Article Comparative Study of Atmospheric and Submerged AWJM Performance on Nimonic-90 Superalloy: Depth of Penetration Analysis and Hybrid Cohort Intelligence Modeling Dilip Maruthi G, Sudhakar C Jambagi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8993328/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract This research investigates the performance of Abrasive Water Jet Machining (AWJM) on the Nimonic 90 superalloy, specifically focusing on the influence of operational environment, atmospheric versus submerged, on the Depth of Penetration (DOP) and resulting surface finish. Experimental analysis revealed that atmospheric machining resulted in a higher maximum DOP of \((\mathbf{37.46 \pm 3.01 \, \text{mm}})\) (at \((275 \, \text{MPa})\) ), while the submerged condition consistently produced a smoother surface finish ( \((R_a)\) range: \((1.91)\) to \((4.45 \, \mathbf{\mu m})\) ) due to the water's damping effect. Traverse Speed (TS) was identified as the most dominant control factor for DOP ( \((\Delta = 6.36)\) ), where increasing TS by \((\sim 45%)\) caused a considerable reduction in penetration. For predictive modeling, a novel hybrid algorithm integrating Cohort Intelligence (CI) with linear regression was developed, exhibiting exceptional accuracy, particularly under submerged conditions, with a Pearson correlation coefficient ( \((\mathbf{R^2})\) ) of \((\mathbf{0.9863})\) and a low MSE ( \((\mathbf{MSE})\) ) of \((\mathbf{0.750})\) . This research validates SAWJM as a robust, low-noise alternative for machining Nimonic 90 when surface integrity is prioritized over maximum depth, and it offers a highly accurate hybrid model for process optimization Physical sciences/Engineering Earth and environmental sciences/Environmental sciences Abrasive Water Jet Machining Submerged Abrasive Water Jet Machining Cohort intelligence Depth of penetration Hybrid algorithm Nimonic 90 Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 21 Apr, 2026 Reviews received at journal 05 Apr, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviews received at journal 25 Mar, 2026 Reviewers agreed at journal 23 Mar, 2026 Reviews received at journal 22 Mar, 2026 Reviewers agreed at journal 22 Mar, 2026 Reviewers invited by journal 19 Mar, 2026 Editor assigned by journal 19 Mar, 2026 Editor invited by journal 17 Mar, 2026 Submission checks completed at journal 04 Mar, 2026 First submitted to journal 04 Mar, 2026 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. 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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-8993328","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":608726345,"identity":"fd4eee98-7c0c-4cb1-9763-e088e8fb0e34","order_by":0,"name":"Dilip Maruthi G","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYFCCBAjJLwEXYWwgTovkDJK1GNwg1lny7tkJTDcq7PKMb3cnf/hRwSDP38Dc9gCfFsMzbzcw55xJLja7c3abZM8ZBsMZBxjbDfBqmZG7gTm37UDithu525gZ2xgYNzAwtkkQ1vLvQOLmGbmbPzP+Y7AnqEVeAqSl4UDiBiBDGhhWiQS1GPC83XA451hy4gywX45JJM84TMiW9tyNj3Nq7BL7Z/du/vCjxsa2v739GX5bDjAwHEDiAxUz41MPsqWBgIJRMApGwSgYBQwAQ7xOGCSzJAcAAAAASUVORK5CYII=","orcid":"","institution":"BMS College Of Engineering","correspondingAuthor":true,"prefix":"","firstName":"Dilip","middleName":"Maruthi","lastName":"G","suffix":""},{"id":608726349,"identity":"af10209e-16f2-4831-b1e9-6d8b2809ad40","order_by":1,"name":"Sudhakar C Jambagi","email":"","orcid":"","institution":"National Institute of Technology Karnataka","correspondingAuthor":false,"prefix":"","firstName":"Sudhakar","middleName":"C","lastName":"Jambagi","suffix":""}],"badges":[],"createdAt":"2026-02-28 08:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8993328/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8993328/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105563859,"identity":"b7ac32c5-c979-4d5c-96fa-7aa2aa77450d","added_by":"auto","created_at":"2026-03-27 12:48:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5069297,"visible":true,"origin":"","legend":"","description":"","filename":"ArticleTitle.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8993328/v1_covered_09360ec5-0d5c-4029-98a8-1b6ea9d7e331.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Study of Atmospheric and Submerged AWJM Performance on Nimonic-90 Superalloy: Depth of Penetration Analysis and Hybrid Cohort Intelligence Modeling","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Abrasive Water Jet Machining, Submerged Abrasive Water Jet Machining, Cohort intelligence, Depth of penetration, Hybrid algorithm, Nimonic 90","lastPublishedDoi":"10.21203/rs.3.rs-8993328/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8993328/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis research investigates the performance of Abrasive Water Jet Machining (AWJM) on the Nimonic 90 superalloy, specifically focusing on the influence of operational environment, atmospheric versus submerged, on the Depth of Penetration (DOP) and resulting surface finish. Experimental analysis revealed that atmospheric machining resulted in a higher maximum DOP of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\mathbf{37.46 \\pm 3.01 \\, \\text{mm}})\\)\u003c/span\u003e\u003c/span\u003e (at \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((275 \\, \\text{MPa})\\)\u003c/span\u003e\u003c/span\u003e), while the submerged condition consistently produced a smoother surface finish (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((R_a)\\)\u003c/span\u003e\u003c/span\u003e range: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((1.91)\\)\u003c/span\u003e\u003c/span\u003e to \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((4.45 \\, \\mathbf{\\mu m})\\)\u003c/span\u003e\u003c/span\u003e) due to the water's damping effect. Traverse Speed (TS) was identified as the most dominant control factor for DOP (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\Delta = 6.36)\\)\u003c/span\u003e\u003c/span\u003e), where increasing TS by \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\sim 45%)\\)\u003c/span\u003e\u003c/span\u003e caused a considerable reduction in penetration. For predictive modeling, a novel hybrid algorithm integrating Cohort Intelligence (CI) with linear regression was developed, exhibiting exceptional accuracy, particularly under submerged conditions, with a Pearson correlation coefficient (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\mathbf{R^2})\\)\u003c/span\u003e\u003c/span\u003e) of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\mathbf{0.9863})\\)\u003c/span\u003e\u003c/span\u003e and a low MSE (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\mathbf{MSE})\\)\u003c/span\u003e\u003c/span\u003e) of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\\mathbf{0.750})\\)\u003c/span\u003e\u003c/span\u003e. This research validates SAWJM as a robust, low-noise alternative for machining Nimonic 90 when surface integrity is prioritized over maximum depth, and it offers a highly accurate hybrid model for process optimization\u003c/p\u003e","manuscriptTitle":"Comparative Study of Atmospheric and Submerged AWJM Performance on Nimonic-90 Superalloy: Depth of Penetration Analysis and Hybrid Cohort Intelligence Modeling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-23 03:03:54","doi":"10.21203/rs.3.rs-8993328/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-21T06:12:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-05T07:16:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176925577798929483559603996234887785592","date":"2026-03-31T04:36:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-25T10:35:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259899997050663307207183305819883001142","date":"2026-03-23T08:09:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-23T03:04:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25565140510839387579992207512046847674","date":"2026-03-23T02:55:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T07:09:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-19T07:06:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-17T04:52:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-04T14:00:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-04T09:21:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f340df9c-ef61-419f-8632-4e740e59776f","owner":[],"postedDate":"March 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":64775905,"name":"Physical sciences/Engineering"},{"id":64775906,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-05-18T05:08:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-23 03:03:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8993328","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8993328","identity":"rs-8993328","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}