Method of designing the wing airfoil of a transonic transport aircraft based on consequential mathematical modeling and parametric optimization

 
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Abstract

Context and relevance. The tasks of designing wing airfoils for prospective aircraft require the creation of methods that take into account modern requirements for aerodynamic characteristics. At the same time, the proposed procedures should be based on the accumulated experience of designers and engineers in order to take into account all limitations and features. Objective. The first objective is to formulate the airfoil design problem as a parametric optimization task. The second objective is to form an optimization process based on mathematical modeling of the airfoil flow to calculate the values of the objective function and a group of metaheuristic algorithms for searching for a conditional extremum. Hypothesis. The paper assumes that the airfoil geometry can be approximated using expansions in Bernstein polynomials. Methods and materials. In the article, the description of the upper and lower surface using the expansion in terms of the Bernstein polynomial system is used to parameterize the airfoil geometry. The parameters defining the airfoil are the expansion coefficients. To find their values, the designer specifies a set of airfoil base points, as well as segments of possible values of their coordinates. In this case, the constraints on the airfoil thickness and the curvature of the upper surface should also be taken into account. The problem of finding the profile parameters is formulated as a problem of conditional optimization with interval constraints on the designed parameters. The objective function characterizes the degree of satisfaction of the requirements for the integral aerodynamic characteristics. Its values are calculated based on the information obtained using the solver. To transfer information about the current profile geometry to the solver, a geometric model is formed. The optimization problem is solved using a group of metaheuristic algorithms applied sequentially. These include methods simulating the behavior of a swarm of moths, the method of sequential reduction of the search area, and the path-relinking method. A step-by-step technique for solving the wing airfoil design problem is formed. Results. The RAE 5213 airfoil was adopted as the initial airfoil. The airfoil obtained as a result of solving the optimization problem satisfies the requirements specified by the designer in terms of both geometric and aerodynamic characteristics. Conclusions. A method for designing an aerodynamic airfoil is proposed, which consists in finding the coordinates of its base points used for their approximation by the CST method, in order to obtain the required aerodynamic and geometric characteristics of the airfoil. The scientific novelty of the proposed method lies in the fact that the problem of finding the base points of the airfoil is reduced to the problem of sequential finite-dimensional optimization, which is solved using a set of metaheuristic algorithms for finding a conditional global extremum, where the value of the objective function is found using a specialized solver that implements the procedure for mathematical modeling of the process of flow around the airfoil. The obtained results form the basis for the subsequent stage of designing the theoretical wing contour when solving the problem of flow around the full configuration of the aircraft.

General Information

Keywords: wing airfoil design, airfoil parameterization, wing polar, metaheuristic optimization algorithms, mathematical modeling, optimization methods

Journal rubric: Optimization Methods

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2025150304

Received 22.07.2025

Revised 31.07.2025

Accepted

Published

For citation: Panteleev, A.V., Gunchin, V.K., Nadorov, I.S., Akhmedov, I.A. (2025). Method of designing the wing airfoil of a transonic transport aircraft based on consequential mathematical modeling and parametric optimization. Modelling and Data Analysis, 15(3), 56–75. (In Russ.). https://doi.org/10.17759/mda.2025150304

© Panteleev A.V., Gunchin V.K., Nadorov I.S., Akhmedov I.A., 2025

License: CC BY-NC 4.0

References

  1. Болсуновский, А.Л., Бузоверя, Н.П., Карась, О.В., Ковалёв, В.Е. (2002). Развитие методов аэродинамического проектирования крейсерской компоновки дозвуковых самолетов. В: XIII Школа-семинар «Аэродинамика летательных аппаратов» (с. 20), (п. Володарского, 28 февраля – 01 марта 2002 г.). Жуковский: Центральный аэрогидродинамический институт им. профессора Н.Е. Жуковского. https://www.elibrary.ru/item.asp?edn=wcjzgf&ysclid=mcyuoughuz755233486 (дата обращения: 11.07.2025)
    Bolsunovsky, A.L., Buzoverya, N.P., Karas, O.V., Kovalev, V.E. (2002). Development of methods of aerodynamic design of cruise configuration of subsonic aircraft. In: XIII School-seminar "Aerodynamics of aircraft" (pp. 20), (p. Voldarsky, February 28 – March 1, 2002). Zhukovsky: Central Aerohydrodynamic Institute named after Professor N.E. Zhukovsky. (In Russ.). https://www.elibrary.ru/item.asp?edn=wcjzgf&ysclid=mcyuoughuz755233486 (viewed: 11.07.2025)
  2. Болсуновский, А.Л., Бузоверя, Н.П., Скоморохов, C.И., Чернышёв, И.Л. (2018). Расчетно-экспериментальные исследования скоростных крыльев перспективных магистральных самолетов. Труды МАИ, (101). https://www.elibrary.ru/item.asp?id=36300463&ysclid= mcyuvc9et7377343184 (дата обращения: 11.07.2025)
    Bolsunovskii, A.L., Buzoverya, N.P., Skomorokhov, S.I., Chernyshev, I.L. (2018). Computational and experimental studies of high-speed wings for advanced long-haul aircraft. Trudy MAI, (101). (In Russ.). https://www.elibrary.ru/item.asp?id=36300463&ysclid=mcyuvc9et7377343184 (viewed: 11.07.2025)
  3. Гантмахер, Ф.Р. (2010). Теория матриц. М.: Физматгиз.
    Gantmakher, F.R. (2010). Matrix Theory. M.: Fizmatgiz. (In Russ.)
  4. Пантелеев, А.В., Надоров, И.С. (2025). Применение модификации метода, имитирующего поведение стаи мотыльков, для решения задачи оптимального программного управления мобильным роботом. Моделирование и анализ данных, 15(1), с. 81–109. DOI: 10.17759/mda.2025150105
    Panteleev, A.V., Nadorov, I.S. (2025). Application of the modified method simulating the behavior of a flock of moths to solve the optimal open loop control problem of a mobile robot movement. Modelling and Data Analysis, 15(1), pp. 81–109. DOI: https://doi.org/10.17759/mda.2025150105 (In Russ., аbstr. in Engl.)
  5. Пантелеев, А.В., Скавинская, Д.В. (2023). Метаэвристические стратегии и алгоритмы глобальной оптимизации. М.: Факториал.
    Panteleev, A.V., Skavinskaya, D.V. (2023). Metaheuristic strategies and algorithms for global optimization. Moscow: Factorial. (In Russ.)
  6. Пейгин, С.В., Пущин, Н.А., Болсуновский, А.Л., Тимченко, С.В. (2018). Оптимальное аэродинамическое проектирование крыла широкофюзеляжного дальнемагистрального самолета. Вестн. Томск. гос. ун-та. Матем. и мех, (51), с. 117–129. DOI: 10.17223/19988621/51/10
    Peygin, S.V., Pushchin, N.A., Bolsunovskiy, A.L., Timchenko, S.V. (2018). An optimal aerodynamic design for the wing of a wide-body long-range aircraft. Vestnik Tomskogo gosudarstvennogo universiteta. Matematika i mekhanika, (51), pp. 117–129. (In Russ.). DOI 10.17223/19988621/51/10
  7. Akram, M.T., Kim, M.-H. (2021). Aerodynamic shape optimization of NREL S809 airfoil for wind turbine blades using Reynolds-Averaged Navier Stokes Model — Part II. Appl. Sci, 11(5), pp. 2211. https://doi.org/10.3390/app11052211
  8. Epstein, B., Peigin, S. (2005). Constrained aerodynamic optimization of three-dimensional wings driven by Navier-Stokes computations. AIAA Journal, 43(9), pp. 1946–1957. DOI: 10.2514/1.10308
  9. Gardner, B.A., Selig, M.S. (2003). Airfoil design using a genetic algorithm and an inverse method. In: 41st Aerospace Sciences Meeting and Exhibit (6–9 January 2003, AIAA 2003–0043). Reno, Nevada.
  10. Khurana, M.S., Winarto, H., Sinha, A.K. (2008). Airfoil geometry parameterization through shape optimizer and computational fluid dynamics. In: 46th AIAA Aerospace Sciences Meeting and Exhibit (January 2008). DOI: 10.2514/6.2008-295
  11. Koo, D., Zingg, D.W. (2016). Progress in aerodynamic shape optimization based on the Reynolds-averaged Navier-Stokes equations. In: 54th AIAA Aerospace Sciences Meeting (January 2016, AIAA-2016-1292). San Diego, California.
  12. Kulfan, B.M. (2008). A Universal parametric geometry representation method – “CST”.  Journal of Aircraft, 45(1). DOI: 10.2514/1.29958
  13. Kulfan, B.M. (2006). Aerodynamic of sonic flight. Research & Enabling Technology Boeing Commercial Airplanes.
  14. Kulfan, B.M., Bussoletti, J.E. (2006). "Fundamental" parametric geometry representations for aircraft component shapes. In: 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference: The Modeling and Simulation Frontier for Multidisciplinary Design Optimization (6 – 8 September 2006, AIAA-2006-6948). Portsmouth, Virginia.
  15. Kulfan, B.M., Bussoletti, J.E., Hilmes, C.L. (2007). Pressures and drag characteristics of bodies of revolution at near sonic speeds including the effects of viscosity and wind tunnel walls. In: 45th AIAA Aerospace Sciences Meeting and Exhibit (8 – 11 Jan 2007, AIAA-2007-0684). Reno, Nevada. 2007. DOI: 10.2514/6.2007-684
  16. Kulfan, B.M. (2020). Modification of CST airfoil representation methodology. https://www.researchgate.net/publication/343615711
  17. Kulfan, B.M. (2007). Recent extensions and applications of the “CST” universal parametric geometry representation method. In: 7th AIAA Aviation Technology, Integration, and Operations (ATIO) (18-20 September 2007, AIAA-2007-7709). Belfast, Northern Ireland.
  18. Lane, K.L., Marshall, D.D. (2009). A Surface parameterization method for airfoil optimization and high lift 2D geometries utilizing the CST methodology. In: 47th AIAA Aerospace Sciences Meeting Including The New Horizons Forum and Aerospace Exposition (5 - 8 January 2009, AIAA 2009-1461). Orlando, Florida.
  19. Lee, C., Koo, D., Zingg, D.W. (2017). Comparison of B-spline surface and free-form deformation geometry control for aerodynamic optimization. AIAA Journal, 55, pp. 228–240.
  20. Luus, R. (2000). Iterative Dynamic Programming. London, Chapman & Hall/CRC.
  21. Masters, D.A., Taylor, N.J., Rendall, T.C.S., Allen, C.B., Poole, D.J. (2016). A Geometric comparison of aerofoil shape parameterisation methods. In: 54th AIAA Aerospace Sciences Meeting (4–8 January 2016, AIAA 2016-0558). San Diego, California, USA.
  22. Masters, D.A., Taylor, N.J., Rendall, T.C.S., Allen, C.B., Poole, D.J. (2015). Review of aerofoil parameterisation methods for aerodynamic shape optimisation. In: 53rd AIAA Aerospace Sciences Meeting (Jan 2015).
  23. Meheut, M., Dumont, A., Carrier, G., Peter, J.E. (2016). Gradient-based optimization of CRM wing-alone and wingbody-tail configurations by RANS adjoint technique. In: 54th AIAA Aerospace Sciences Meeting (January 2016, AIAA-2016-1293). San Diego, California.
  24. Mirjalili, S. (2015). Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems, 89, pp. 228–249.
  25. Peigin, S., Epstein, B. (2004). Robust handling of non-linear constraints for GA optimization of aerodynamic shapes. International Journal for Numerical Methods in Fluids, 45(12), pp. 1339–1362. DOI: 10.1002/fld.747
  26. Poole, D.J., Allen, C.B., Rendall, T.C.S. (2015). Optimal domain element shapes for free-form aerodynamic shape control. In: Session: Aerodynamic Design: Analysis, Methodologies & Optimization Techniques II (3 Jan 2015, AIAA 2015-0762). https://doi.org/10.2514/6.2015-0762
  27. Sederberg, T.W., Parry, S.R. (1986). Free-form deformation of solid geometric models. In: 13th Annual Conference on Computer Graphics and Interactive Techniques (no. 4, pp. 151-160). Dallas, Texas.
  28. Sobieczky, H. (1998). Parametric airfoils and wings. Notes on Numerical Fluid Mechanics, 68, pp. 71–87. Vieweg Verlag.
  29. Toal, D.J.J., Bresslo, N.W., Keane, A.J. (2010). Geometric filtration using proper orthogonal decomposition for aerodynamic design optimization. AIAA Journal, 48(5), pp. 916–928.
  30. Zhu, F. (2014). Geometric parameterisation and aerodynamic shape optimisation. PhD thesis, University of Sheffield. 
  31. Zhu, F., Qin, N. (2014). Intuitive class/shape function parameterization for airfoils. AIAA Journal, 52(1), pp. 17–25.
  32. Пантелеев, А.В., Гунчин, В.К., Надоров, И.С., Ахмедов, И.А., Силаев Н.А. (2025). Методы параметрической оптимизации в задаче проектирования характерных профилей крыла трансзвукового транспортного самолета. Труды МАИ, (142). URL: https://trudymai.ru/ published.php?ID=185117
    Panteleev, A.V., Gunchin, V.K., Nadorov, I.S., Akhmedov, I.A., Silaev N.A. (2025) Parametric optimization methods in a transonic transport aircraft characteristic wings airfoils designing problem. Trudy MAI, (142). (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=185117

Information About the Authors

Andrey V. Panteleev, Doctor of Physics and Matematics, Professor, Professor, Head of the Department of Mathematical Cybernetics, Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0003-2493-3617, e-mail: avpanteleev@inbox.ru

Vitalyi K. Gunchin, Engineer, Center for Composite Structures, Moscow Aviation Institute (national research university) (MAI), Moscow, Russian Federation, e-mail: gunchinvk@mai.ru

Ivan S. Nadorov, Assistant professor of the Department of Mathematics and Cybernetics, Institute "Computer Science and Applied Mathematics", Moscow Aviation Institute (National Research University), Moscow, Russian Federation, ORCID: https://orcid.org/0009-0008-2085-2987, e-mail: nnadorovivan@gmail.com

Isak A. Akhmedov, Engineer, Center for Composite Structures, Moscow Aviation Institute (national research university) (MAI), Moscow, Russian Federation, e-mail: ahmedovisak@gmail.com

Contribution of the authors

Andrei V. Panteleev — Conceptualization, Supervision, Methodology, Writing – Original Draft Preparation.

Vitalyi K. Gunchin — Conceptualization, Methodology, Writing – Original Draft Preparation, Vis-ualization.

Ivan S. Nadorov — Software, Writing – Original Draft Preparation, Visualization.

Isak A. Akhmedov — Software, Visualization.

All authors participated in the discussion of the results and approved the final text of the manu-script.

Conflict of interest

The authors declare no conflict of interest.

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