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{"work":{"id":31708898,"created_at":"2017-03-04T07:51:19.679-08:00","from_world_paper_id":161154927,"updated_at":"2024-11-18T05:56:11.319-08:00","_data":{"grobid_abstract":"A gradient-based optimization method for minimization of the total drag of an airfoil is presented. The viscous drag is minimized by delaying the laminarturbulent transition. The gradients are obtained solving the adojoint of the Euler, boundary-layer and stability equations. The optimization is subjected to constraints such as restrictions on geometry, lift and pitch moment. The geometry is parametrised using radial basis functions.","publication_date":"2009,,","publication_name":"IUTAM Bookseries","grobid_abstract_attachment_id":"52023088"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"A Gradient-based Optimization Method for Natural Laminar Flow Design","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [60938844]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; window.loswp.useOptimizedScribd4genScript = false; window.loginModal = {}; window.loginModal.appleClientId = 'edu.academia.applesignon'; window.userInChina = "false";</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":52023088,"attachmentType":"pdf"}"><img alt="First page of “A Gradient-based Optimization Method for Natural Laminar Flow Design”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/52023088/mini_magick20190123-29407-1asilri.png?1548302979" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/images/single_work_splash/adobe_icon.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">A Gradient-based Optimization Method for Natural Laminar Flow Design</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="60938844" href="https://independent.academia.edu/OlivierAmoignon"><img alt="Profile image of Olivier Amoignon" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/60938844/144425964/133949491/s65_olivier.amoignon.png" />Olivier Amoignon</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2009, IUTAM Bookseries</p><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">8 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 31708898; const worksViewsPath = "/v0/works/views?subdomain_param=api&work_ids%5B%5D=31708898"; const getWorkViews = async (workId) => { const response = await fetch(worksViewsPath); if (!response.ok) { throw new Error('Failed to load work views'); } const data = await response.json(); return data.views[workId]; }; // Get the view count for the work - we send this immediately rather than waiting for // the DOM to load, so it can be available as soon as possible (but without holding up // the backend or other resource requests, because it's a bit expensive and not critical). const viewCount = await getWorkViews(workId); const updateViewCount = (viewCount) => { try { const viewCountNumber = parseInt(viewCount, 10); if (viewCountNumber === 0) { // Remove the whole views element if there are zero views. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); return; } const commaizedViewCount = viewCountNumber.toLocaleString(); const viewCountBody = document.getElementById('work-metadata-view-count'); if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">A gradient-based optimization method for minimization of the total drag of an airfoil is presented. The viscous drag is minimized by delaying the laminarturbulent transition. The gradients are obtained solving the adojoint of the Euler, boundary-layer and stability equations. The optimization is subjected to constraints such as restrictions on geometry, lift and pitch moment. The geometry is parametrised using radial basis functions.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":52023088,"attachmentType":"pdf","workUrl":"https://www.academia.edu/31708898/A_Gradient_based_Optimization_Method_for_Natural_Laminar_Flow_Design"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":52023088,"attachmentType":"pdf","workUrl":"https://www.academia.edu/31708898/A_Gradient_based_Optimization_Method_for_Natural_Laminar_Flow_Design"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div><div class="ds-signup-banner-trigger-container"><div class="ds-signup-banner-trigger ds-signup-banner-trigger-control"></div></div><div class="ds-signup-banner ds-signup-banner-control"><div id="ds-signup-banner-close-button"><button class="ds2-5-button ds2-5-button--secondary ds2-5-button--inverse"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">close</span></button></div><div class="ds-signup-banner-ctas" data-impression-entity-id="31708898" data-impression-entity-type="2" data-impression-source="signup-banner"><img src="//a.academia-assets.com/images/academia-logo-capital-white.svg" /><h4 class="ds2-5-heading-serif-sm">Sign up for access to the world's latest research</h4><button class="ds2-5-button ds2-5-button--inverse ds2-5-button--full-width js-swp-download-button" data-signup-modal="{"location":"signup-banner"}">Sign up for free<span class="material-symbols-outlined" style="font-size: 20px" translate="no">arrow_forward</span></button></div><div class="ds-signup-banner-divider"></div><div class="ds-signup-banner-reasons"><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Get notified about relevant papers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Save papers to use in your research</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Join the discussion with peers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Track your impact</span></div></div></div><script>(() => { // Set up signup banner show/hide behavior: // 1. 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The viscous drag is minimized by delaying the laminarturbulent transition. The gradients are obtained solving the adojoint of the Euler, boundary-layer and stability equations. The optimization is subjected to constraints such as restrictions on geometry, lift and pitch moment. The geometry is parametrised using radial basis functions.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Gradient-based Optimization Method for Natural Laminar Flow Design : OPTLAM Project Final Report","attachmentId":52023083,"attachmentType":"pdf","work_url":"https://www.academia.edu/31708901/A_Gradient_based_Optimization_Method_for_Natural_Laminar_Flow_Design_OPTLAM_Project_Final_Report","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/31708901/A_Gradient_based_Optimization_Method_for_Natural_Laminar_Flow_Design_OPTLAM_Project_Final_Report"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="69712577" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/69712577/Aerodynamic_Optimization_of_an_Airfoil_Using_Gradient_Based_Method">Aerodynamic Optimization of an Airfoil Using Gradient Based Method</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="59401597" href="https://independent.academia.edu/MasoudMirzaei6">Masoud Mirzaei</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2006</p><p class="ds-related-work--abstract ds2-5-body-sm">A gradient based method is presented for optimization of an airfoil configuration. The flow is governed by two dimensional, compressible Euler equations. A finite volume code based on unstructured grid is developed to solve the equations. The procedure is carried out for optimizing an airfoil with initial configuration of NACA 0012. The advantage of this technique over the other gradient based methods is its speed of converging.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Aerodynamic Optimization of an Airfoil Using Gradient Based Method","attachmentId":79703289,"attachmentType":"pdf","work_url":"https://www.academia.edu/69712577/Aerodynamic_Optimization_of_an_Airfoil_Using_Gradient_Based_Method","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/69712577/Aerodynamic_Optimization_of_an_Airfoil_Using_Gradient_Based_Method"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="63921619" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/63921619/Gradient_Based_Aerodynamic_Optimization_of_an_Airfoil_with_Morphing_Leading_and_Trailing_Edges">Gradient-Based Aerodynamic Optimization of an Airfoil with Morphing Leading and Trailing Edges</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="66766086" href="https://independent.academia.edu/AlessandroGaspari">Alessandro Gaspari</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Applied Sciences</p><p class="ds-related-work--abstract ds2-5-body-sm">This article presents a gradient-based aerodynamic optimization framework and investigates optimum deformations for a transonic airfoil equipped with morphing leading and trailing edges. Specifically, the proposed optimization framework integrates an innovative morphing shape parameterization with a high fidelity Reynolds-averaged Navier–Stokes computational fluid dynamic solver, a hybrid mesh deformation algorithm, and an efficient gradient evaluation method based on continuous adjoint implementation. To achieve a feasible morphing shape, some structural properties of skin and wing-box constraints were introduced into the morphing shape parameterization, which offers skin length control and enables wing-box shape invariance. In this study, the optimum leading and trailing edge deformations with minimization of drag at this cruise stage were searched for using the adjoint-based optimization with a nested feasible morphing procedure, subject to the wing-box, skin length, and airfoil ...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Gradient-Based Aerodynamic Optimization of an Airfoil with Morphing Leading and Trailing Edges","attachmentId":76183624,"attachmentType":"pdf","work_url":"https://www.academia.edu/63921619/Gradient_Based_Aerodynamic_Optimization_of_an_Airfoil_with_Morphing_Leading_and_Trailing_Edges","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/63921619/Gradient_Based_Aerodynamic_Optimization_of_an_Airfoil_with_Morphing_Leading_and_Trailing_Edges"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="28049689" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/28049689/Airfoil_Optimization_Using_Practical_Aerodynamic_Design_Requirements">Airfoil Optimization Using Practical Aerodynamic Design Requirements</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="52582100" href="https://independent.academia.edu/HowardBuckley">Howard Buckley</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Aircraft, 2010</p><p class="ds-related-work--abstract ds2-5-body-sm">Practical aerodynamic design problems must balance the goal of performance optimization over a range of on-design operating conditions with the need to meet design constraints at various off-design operating conditions. Such design problems can be cast as multipoint optimization problems where the on-design and off-design operating conditions are represented as design points with corresponding objective/constraint functions. Two methods are presented for obtaining optimal airfoil designs that satisfy all design objectives and constraints. The first method uses an unconstrained optimization algorithm where the optimal design is achieved by minimizing a weighted sum of the objective functions at each of the operating conditions. To address the competing design objectives between on-design and off-design operating conditions, an automated procedure is used to efficiently weight the off-design objective functions so as to limit their influence on the overall optimization while satisfying the design constraints. The second method uses the constrained optimization algorithm SNOPT, which allows the aerodynamic constraints imposed at the off-design operating conditions to be treated explicitly. Both methods are applied to the design of an airfoil for a hypothetical aircraft where the problem is formulated as an 18-point multipoint optimization. * Graduate Student, howard@oddjob.utias.utoronto.ca † Undergraduate Student, Student Member AIAA, beckett@oddjob.utias.utoronto.ca ‡ Professor, Tier I Canada Research Chair in Computational Aerodynamics, Associate Fellow AIAA,</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Airfoil Optimization Using Practical Aerodynamic Design Requirements","attachmentId":48360380,"attachmentType":"pdf","work_url":"https://www.academia.edu/28049689/Airfoil_Optimization_Using_Practical_Aerodynamic_Design_Requirements","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/28049689/Airfoil_Optimization_Using_Practical_Aerodynamic_Design_Requirements"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="8079625" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/8079625/CFD_Based_Wing_Shape_Optimization_Through_Gradient_Based_Method">CFD Based Wing Shape Optimization Through Gradient-Based Method</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="15615704" href="https://independent.academia.edu/santiagogiraldo2">santiago giraldo</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2008</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper deals with the optimization of shape of aerodynamic profiles. The objective is to reduce the drag coefficient on a given airfoil while preserving the lift coefficient within acceptable ranges. A set of control points defining the geometry are passed and parameterized as a B-Spline curve. These points are modified automatically by means of CFD analysis. A given shape is defined by an user and a valid volumetric CFD domain is constructed from this planar data and a set of user-defined parameters. The construction process involves the usage of 2D and 3D meshing algorithms that were coupled into owncode. The volume of air surrounding the airfoil and mesh quality are also parametrically defined. Some standard NACA profiles were used by obtaining first its control points in order to test the algorithm.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"CFD Based Wing Shape Optimization Through Gradient-Based Method","attachmentId":34531840,"attachmentType":"pdf","work_url":"https://www.academia.edu/8079625/CFD_Based_Wing_Shape_Optimization_Through_Gradient_Based_Method","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/8079625/CFD_Based_Wing_Shape_Optimization_Through_Gradient_Based_Method"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="28049685" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/28049685/Approach_to_Aerodynamic_Design_Through_Numerical_Optimization">Approach to Aerodynamic Design Through Numerical Optimization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="52582100" href="https://independent.academia.edu/HowardBuckley">Howard Buckley</a></div><p class="ds-related-work--metadata ds2-5-body-xs">AIAA Journal, 2013</p><p class="ds-related-work--abstract ds2-5-body-sm">A multipoint optimization approach is used to solve aerodynamic design problems encompassing a broad range of operating conditions in the objective function and constraints. The designer must specify the range of on-design operating conditions, the objective function to be minimized, a weighting function based on the mission or fleet requirements, and a set of performance and geometric constraints. Based on this designer input, a weighted-integral objective function is developed. The numerical optimization problem is then formulated as a constrained multipoint problem with the weight assigned to each operating condition determined by a quadrature rule. The approach is illustrated with several design problems for transonic civil transport aircraft and is extended to the formulation of aircraft range and endurance objective functions for use in the design of an unmanned aerial vehicle. The results demonstrate that the approach enables the designer to design an airfoil that is precisely tailored to the problem specification. Pareto fronts are presented as a means of providing the designer with information on tradeoffs that can be used to guide the problem specification.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Approach to Aerodynamic Design Through Numerical Optimization","attachmentId":48360379,"attachmentType":"pdf","work_url":"https://www.academia.edu/28049685/Approach_to_Aerodynamic_Design_Through_Numerical_Optimization","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/28049685/Approach_to_Aerodynamic_Design_Through_Numerical_Optimization"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="33919805" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/33919805/Airfoil_optimization_with_transition_curve_as_objective_function">Airfoil optimization with transition curve as objective function</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="66524835" href="https://independent.academia.edu/MiguelSilvestre1">Miguel Silvestre</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2013</p><p class="ds-related-work--abstract ds2-5-body-sm">The present work describes the design optimization of a low Reynolds number high lift airfoil where the objective function is that curve defined by the lift coefficient variation with the boundary layer transition position along the upper and lower surfaces of the airfoil. An aerodynamic shape optimization program using XFOIL as the solver, a viscous/inviscid two-dimensional panel method formulation code, and a sequential quadratic programming optimization routine, solves a minimization problem to determine the optimal airfoil geometry which minimizes the difference between its lift coefficient versus transition position curves and the specified objective curves while subject to geometric constraints and constant product of Reynolds number with the square root of lift coefficient for a given interval of lift coefficient values. The airfoil design variables are B-spline control points which define the airfoil camber line and the airfoil thickness distribution. A case study is presented for an airfoil design suitable for a long endurance UAV demonstrating the capability of the approach in producing an optimized design. Comparisons with other objective functions are also shown.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Airfoil optimization with transition curve as objective function","attachmentId":53889805,"attachmentType":"pdf","work_url":"https://www.academia.edu/33919805/Airfoil_optimization_with_transition_curve_as_objective_function","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/33919805/Airfoil_optimization_with_transition_curve_as_objective_function"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="49704528" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/49704528/Optimization_of_Airfoils_for_Minimum_Pitching_Moment_and_Compressibility_Drag_Coefficients">Optimization of Airfoils for Minimum Pitching Moment and Compressibility Drag Coefficients</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="163976146" href="https://independent.academia.edu/HamidFarrokhfal">Hamid Farrokhfal</a></div><p class="ds-related-work--abstract ds2-5-body-sm">This paper concerns a numerical optimization method for designing airfoils based on adjoint method. The goal of present work is to reduce the compressibility drag or pitching moment of transonic airfoils without compromising on the lift coefficient. A new cost function based on this requirement is defined and the corresponding adjoint equations are discussed in details. At the end, by demonstrating some numerical results, we show that this technique is capable of converging to the optimum design point corresponding to the initial geometry of the airfoil.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Optimization of Airfoils for Minimum Pitching Moment and Compressibility Drag Coefficients","attachmentId":67977204,"attachmentType":"pdf","work_url":"https://www.academia.edu/49704528/Optimization_of_Airfoils_for_Minimum_Pitching_Moment_and_Compressibility_Drag_Coefficients","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/49704528/Optimization_of_Airfoils_for_Minimum_Pitching_Moment_and_Compressibility_Drag_Coefficients"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="25148119" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/25148119/Gradient_Based_Aerodynamic_Optimization_with_the_elsA_Software">Gradient-Based Aerodynamic Optimization with the elsA Software</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="48453122" href="https://independent.academia.edu/MichaelMeheut">Michael Meheut</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="48574426" href="https://independent.academia.edu/AntoineDumont2">Antoine Dumont</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="48438319" href="https://independent.academia.edu/JacquesPeter">Jacques Peter</a></div><p class="ds-related-work--metadata ds2-5-body-xs">52nd Aerospace Sciences Meeting, 2014</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper describes the work performed by ONERA and Airbus to solve several aerodynamic optimization problems proposed in 2013 by the AIAA Optimization Discussion Group (ADODG). Three of the four test cases defined by this group have been addressed, respectively a 2D invicid, non-lifting, transonic airfoil optimization problem, a 2D RANS transonic airfoil optimization problem and a 3D RANS transonic wing optimization problem. All three problems have been investigated using local, gradient-based, optimization techniques and the elsA[1][2] CFD software and its adjoint capability. Through these three optimization exercises, several generic issues introduced by aerodynamic gradient-based optimization have been investigated. Among the investigated aspects are the impact of the geometry parameterization (nature and dimension), of the accuracy of the gradient calculation method, optimization algorithm and presence of constraints in the optimization problem.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Gradient-Based Aerodynamic Optimization with the elsA Software","attachmentId":45469055,"attachmentType":"pdf","work_url":"https://www.academia.edu/25148119/Gradient_Based_Aerodynamic_Optimization_with_the_elsA_Software","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/25148119/Gradient_Based_Aerodynamic_Optimization_with_the_elsA_Software"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="674874" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/674874/Comparative_Study_of_Three_Dimensional_Wing_Drag_Minimization_by_Different_Optimization_Techniques">Comparative Study of Three-Dimensional Wing Drag Minimization by Different Optimization Techniques</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="161168" href="https://mta-il.academia.edu/BorisEpstein">Boris Epstein</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Aircraft, 2009</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Comparative Study of Three-Dimensional Wing Drag Minimization by Different Optimization Techniques","attachmentId":51298722,"attachmentType":"pdf","work_url":"https://www.academia.edu/674874/Comparative_Study_of_Three_Dimensional_Wing_Drag_Minimization_by_Different_Optimization_Techniques","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/674874/Comparative_Study_of_Three_Dimensional_Wing_Drag_Minimization_by_Different_Optimization_Techniques"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":52023088,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":52023088,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_52023088" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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