Improved vortex lattice method for drag prediction of supersonic wings using shock cone modelling

Improved vortex lattice method for drag prediction of supersonic wings using shock cone modelling | 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 Improved vortex lattice method for drag prediction of supersonic wings using shock cone modelling Hemant Joshi, Peter Thomas, Christabel Tan, Hongwei Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5418595/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Aug, 2025 Read the published version in Engineering with Computers → Version 1 posted 5 You are reading this latest preprint version Abstract In the realm of supersonic design, obtaining data for numerous supersonic configurations amidst intricate flow conditions proves time-consuming due to the excessive costs associated with high-fidelity computational demands. Running iterative simulations over an extended period is often impractical or entails substantial expenses. This inherent challenge necessitates the adoption of low-order potential solvers with reasonable accuracy to generate datasets. In support of this objective, This study addresses the high computational costs of obtaining data for supersonic configurations by developing a low-order solver that combines the Taylor-Maccoll hypervelocity method (TMHM) with the supersonic vortex lattice method. This approach aims to provide accurate drag predictions in supersonic flows while minimizing computational demands. By integrating TMHM to calculate wave drag and skin friction drag and enhancing the vortex lattice method to handle shockwave impacts through panel matching, the solver achieves improved accuracy in lift and drag computations. Validation against experimental data shows a 20% reduction in drag prediction error compared to traditional vortex lattice methods, with a 2.01% error for low-shock angles. The method achieves accuracy rates between 90% and 95% across various configurations, including a 90% accuracy for delta wings, 85% for positive dihedral wings, and 95% for large sweptback angle designs, as confirmed by comparisons with high-fidelity CFD data. Supersonic Vortex Lattice Method Shockcone Drag Prediction Supersonic Drag Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Aug, 2025 Read the published version in Engineering with Computers → Version 1 posted Reviewers agreed at journal 14 Nov, 2024 Reviewers invited by journal 11 Nov, 2024 Editor assigned by journal 09 Nov, 2024 Submission checks completed at journal 09 Nov, 2024 First submitted to journal 08 Nov, 2024 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-5418595","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":378163727,"identity":"7155f501-7175-417c-aafc-19ede5eef9ce","order_by":0,"name":"Hemant Joshi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACAwaGBAbGBgk7fgmEIDNRWpIlZwB5B4jUwgDUwsC44QaxWswZGB4+/LnDgtn4dvOxzx/+MMjzN/AYG+DTYtnAkGzMe0aCz+zOseQZB9sYDGcc4DFOwOuwAwxp0oxtEsxmN3KMGQ6CXMjAY3yAkBbJn20SjJtn5H9mOPCHwZ4oLRK8QC0bJHKYGQ6wMSSCtOB32GGQX9okkiVupBkznAUyZhxmK8brfYPjPYkPf7bV2fHPSH7MUPHHxra/vXmzBD4tDMw8KK6QIBQrIMB+gKCSUTAKRsEoGOEAAMM8RK7Krg5SAAAAAElFTkSuQmCC","orcid":"","institution":"University of Hertfordshire","correspondingAuthor":true,"prefix":"","firstName":"Hemant","middleName":"","lastName":"Joshi","suffix":""},{"id":378163728,"identity":"560574f9-e729-4411-a7b5-c05d606d8cea","order_by":1,"name":"Peter Thomas","email":"","orcid":"","institution":"University of Hertfordshire","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Thomas","suffix":""},{"id":378163729,"identity":"ef3bb7ff-5623-4653-b9fa-b33ccb4814f4","order_by":2,"name":"Christabel Tan","email":"","orcid":"","institution":"University of Hertfordshire","correspondingAuthor":false,"prefix":"","firstName":"Christabel","middleName":"","lastName":"Tan","suffix":""},{"id":378163730,"identity":"16f94dbe-d33c-4710-945c-5058e96196a8","order_by":3,"name":"Hongwei Wu","email":"","orcid":"","institution":"University of Hertfordshire","correspondingAuthor":false,"prefix":"","firstName":"Hongwei","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2024-11-08 19:53:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5418595/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5418595/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00366-025-02192-2","type":"published","date":"2025-08-13T15:57:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89310662,"identity":"3c05f0dc-e95a-4171-bfcc-632d0179804f","added_by":"auto","created_at":"2025-08-18 16:09:21","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5632476,"visible":true,"origin":"","legend":"","description":"","filename":"MachconeSpringer.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5418595/v1_covered_db34f46d-459f-421f-ae9e-4c69d31cb1b7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Improved vortex lattice method for drag prediction of supersonic wings using shock cone modelling","fulltext":[],"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":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"engineering-with-computers","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ewco","sideBox":"Learn more about [Engineering with Computers](http://link.springer.com/journal/366)","snPcode":"366","submissionUrl":"https://submission.nature.com/new-submission/366/3","title":"Engineering with Computers","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Supersonic Vortex Lattice Method, Shockcone, Drag Prediction, Supersonic Drag","lastPublishedDoi":"10.21203/rs.3.rs-5418595/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5418595/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the realm of supersonic design, obtaining data for numerous supersonic configurations amidst intricate flow conditions proves time-consuming due to the excessive costs associated with high-fidelity computational demands. 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