Generative Shape Optimization of a Rigid Wingsail Aerofoil using Bézier Parameterization and CFD Validation

Generative Shape Optimization of a Rigid Wingsail Aerofoil using Bézier Parameterization and CFD Validation | 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 Generative Shape Optimization of a Rigid Wingsail Aerofoil using Bézier Parameterization and CFD Validation Md. Shihab Mia, S M Rashidul Hasan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8584900/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract With regulatory and market pressure to decarbonize merchant shipping, Wind-Assisted Propulsion Systems (WAPS) have regained attention as a fuel-saving technology. This study presents a generative design workflow for a two-dimensional wingsail aerofoil tailored to low-speed maritime operation. Geometry was parameterized using 9th-order Bézier curves and optimized in MATLAB using a constrained formulation of the fmincon solver with an objective equivalent to maximizing lift-to-drag ratio (CL/CD) under a thin-aerofoil, inviscid formulation. The optimization returned a candidate profile with a theoretical peak CL/CD of 21.51 at 3.23° angle of attack. To account for viscous effects and validate the design, RANS CFD simulations were performed using the SST k–ω turbulence model on a C-grid mesh with y+<1. CFD predicted a peak CL/CD of 40.91 at 20 m s⁻¹ and 3.23° AoA — an improvement of ≈90% relative to the inviscid prediction — and revealed a sensitivity to leading-edge radius that causes stall onset between 10° and 11°. A techno-economic case study for a 35 m × 5-sail retrofit on M.V. BANGLAR ARJAN (transatlantic route) estimates an approximate voyage energy saving of 1.86% under the assumptions stated. We discuss the limitations of inviscid optimization for marine wing sails and recommend integrating viscous models and geometric constraints (minimum leading-edge radius and thickness distribution) in future generative loops. The results demonstrate the practicality of generative Bézier-based optimization for wing sail aerofoil design while identifying specific improvements required for robust operational performance. Physical sciences/Energy science and technology Physical sciences/Engineering Physical sciences/Mathematics and computing Wingsail Aerofoil design Bézier parameterization Generative optimization CFD validation Wind-assisted propulsion Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-8584900","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":592543520,"identity":"683a81d3-2027-4da8-9475-97daa3587649","order_by":0,"name":"Md. 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