Computational Framework for Nonlinear Seakeeping Prediction under Hydrodynamic Uncertainty

Computational Framework for Nonlinear Seakeeping Prediction under Hydrodynamic Uncertainty | 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 Computational Framework for Nonlinear Seakeeping Prediction under Hydrodynamic Uncertainty Monty J Singh, Balwinder Sodhi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8997896/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Seakeeping plays a significant role in the areas of ship design, operability, and safety assessment in dynamic open-sea conditions. One of the primary challenges of computational marine hydrodynamics is the accurate prediction of non-linear seakeep-ing behaviour under irregular wave excitation and operational uncertainty. Existing works use threshold-based criteria for roll,acceleration, slamming and deck wetness which are computed independently and under model-specific assumptions, disregarding computational trade-offs, uncertainty and real-time operational requirements. This study proposes a unified benchmarking and uncertainty-aware framework for non-linear seakeeping prediction that integrates hydrodynamic modelling, proba-bilistic benchmarking, and digital twins. A generic mathematical representation is used to define seakeeping criterion in terms of six-degree-of-freedom vessel dynamics and wave-structure interactions. The paper proposes a composite hydrodynamic risk function that represents the joint occurance of slamming loads,green water events, excessive roll motion, and acceleration breach. Modeling uncertainty arising from wave-spectrum variability, sensor noise, and parameter uncertainty is addressed using probabilistic uncertainty propagation and fine-tuning using data-driven learning. The integration of physics-based hydrodynamic solvers with real-time data assimilation enables dynamic updating of operational safety parameters and non-linear performance prediction.The proposed framework bridges the gap between existing seakeeping theories by leveraging data-driven digital twin design, which serves as a foundation for model selection and future research in computational marine hydro-dynamics. Seakeeping Digital Twins Habitability Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 03 May, 2026 Reviewers agreed at journal 12 Apr, 2026 Reviewers invited by journal 10 Apr, 2026 Editor assigned by journal 15 Mar, 2026 Submission checks completed at journal 05 Mar, 2026 First submitted to journal 28 Feb, 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. 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-8997896","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":621716937,"identity":"bd0b50a2-648f-4047-ba3a-99495fe6f3fe","order_by":0,"name":"Monty J Singh","email":"data:image/png;base64,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","orcid":"","institution":"Indian Institute of Technology Ropar","correspondingAuthor":true,"prefix":"","firstName":"Monty","middleName":"J","lastName":"Singh","suffix":""},{"id":621716939,"identity":"a14a7580-bad8-4155-a474-d304f1a31ab3","order_by":1,"name":"Balwinder Sodhi","email":"","orcid":"","institution":"Indian Institute of Technology Ropar","correspondingAuthor":false,"prefix":"","firstName":"Balwinder","middleName":"","lastName":"Sodhi","suffix":""}],"badges":[],"createdAt":"2026-02-28 21:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8997896/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8997896/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107481457,"identity":"a22ef4f4-7268-4e0c-8392-9ef4896fa542","added_by":"auto","created_at":"2026-04-22 02:18:05","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":516111,"visible":true,"origin":"","legend":"","description":"","filename":"ComputationalFrameworkforNonlinearSeakeepingPredictionunderHydrodynamicUncertainty1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8997896/v1_covered_bc365991-a4e8-468b-8d01-7e1f0d7bae4f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Computational Framework for Nonlinear Seakeeping Prediction under Hydrodynamic Uncertainty","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":"journal-of-ocean-engineering-and-marine-energy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"oeme","sideBox":"Learn more about [Journal of Ocean Engineering and Marine Energy](http://link.springer.com/journal/40722)","snPcode":"40722","submissionUrl":"https://submission.nature.com/new-submission/40722/3","title":"Journal of Ocean Engineering and Marine Energy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Seakeeping, Digital Twins, Habitability","lastPublishedDoi":"10.21203/rs.3.rs-8997896/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8997896/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Seakeeping plays a significant role in the areas of ship design, operability, and safety assessment in dynamic open-sea conditions. One of the primary challenges of computational marine hydrodynamics is the accurate prediction of non-linear seakeep-ing behaviour under irregular wave excitation and operational uncertainty. Existing works use threshold-based criteria for roll,acceleration, slamming and deck wetness which are computed independently and under model-specific assumptions, disregarding computational trade-offs, uncertainty and real-time operational requirements. This study proposes a unified benchmarking and uncertainty-aware framework for non-linear seakeeping prediction that integrates hydrodynamic modelling, proba-bilistic benchmarking, and digital twins. A generic mathematical representation is used to define seakeeping criterion in terms of six-degree-of-freedom vessel dynamics and wave-structure interactions. The paper proposes a composite hydrodynamic risk function that represents the joint occurance of slamming loads,green water events, excessive roll motion, and acceleration breach. Modeling uncertainty arising from wave-spectrum variability, sensor noise, and parameter uncertainty is addressed using probabilistic uncertainty propagation and fine-tuning using data-driven learning. The integration of physics-based hydrodynamic solvers with real-time data assimilation enables dynamic updating of operational safety parameters and non-linear performance prediction.The proposed framework bridges the gap between existing seakeeping theories by leveraging data-driven digital twin design, which serves as a foundation for model selection and future research in computational marine hydro-dynamics.","manuscriptTitle":"Computational Framework for Nonlinear Seakeeping Prediction under Hydrodynamic Uncertainty","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-17 13:47:33","doi":"10.21203/rs.3.rs-8997896/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-03T15:58:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"335754123466887357475588069445888590626","date":"2026-04-12T14:25:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-10T12:04:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-15T15:55:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-05T17:47:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Ocean Engineering and Marine Energy","date":"2026-02-28T20:55:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-ocean-engineering-and-marine-energy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"oeme","sideBox":"Learn more about [Journal of Ocean Engineering and Marine Energy](http://link.springer.com/journal/40722)","snPcode":"40722","submissionUrl":"https://submission.nature.com/new-submission/40722/3","title":"Journal of Ocean Engineering and Marine Energy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"15a23dd0-c367-407a-8ea0-5c4ebdad793d","owner":[],"postedDate":"April 17th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-03T15:58:25+00:00","index":11,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-17T13:47:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-17 13:47:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8997896","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8997896","identity":"rs-8997896","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}