Helicopter airfoil design using the PGT technique


Аuthors

Nikolsky A. A.

Central Aerohydrodynamic Institute named after N.E. Zhukovsky (TsAGI), 1, Zhukovsky str., Zhukovsky, Moscow Region, 140180, Russia

e-mail: anikolskii@mail.ru

Abstract

The purpose of the presented work consists in creating prospective approach to the airfoil design. A technique with no analogues, namely PGT (parent function generating) technique, which represents a universal geometry parameterization tool and ensures design space in the form of physical region on a plane, bounded by the two monotonous curves, is used for this purpose.

This tool is being combined with the solvers of various accuracy to exploit its advantages. The other purpose consists in studying the contour approximation accuracy to determine the necessary number of the design variables enough for the airfoil aerodynamic design.

Methodology consists in applying the PGT technique, including generating functions, a universal parent function and the two extra parameters to the aerodynamic design problem. At the start, the initial design space is reduced by employing the low-level substantiated solver for local optimization problems solving. Then the process is continuing in reduced space with the high-level solver. Two types of the generating functions approximation are being discussed for the number of the design variables selection.

As the result, the two-step procedure is appeared to be much less consuming than the single-step one. It requires about 100 iterations with high estimated cost and about 1000 iterations with low estimated cost.

Despite this, the demonstrating example of helicopter airfoil design demonstrates the possibility of significant improving of the targeted aerodynamic performance.

The presented study revealed that the original PGT technique allowed significant improvement of the results achieved at the previous level of the aerodynamic design, and, probably, achieving an optimum near the global optimum. In conjunction with the two-stage strategy, it significantly enhances computational effectiveness of the aerodynamic design procedure.

The fact that the PGT technique may be applied in the 3D problems for aerodynamic objects of the wing or fuselage type seems to be of great importance.

Keywords:

PGT technique, aerodynamic design, airfoil, approximation, optimization, wing

References

  1. Bolsunovskii A.L., Buzoverya N.P., Karas' O.V., Kovalev V.E. Trudy TsAGI, 2002, no. 2655, pp. 133-145.

  2. Leoviriyakit K., Jameson A. Aerodynamic shape optimization of wings including planform variables, 41st Aerospace Sciences Meeting & Exhibit, AIAA paper 2003-0210, Reno, Nevada, 2003.

  3. Lyu G.K., Kenway G., Martins J.R., Aerodynamic shape optimization investigations of the common research model wing benchmark, AIAA Journal, 2014, vol. 53, no. 4, pp. 968–985. DOI: 10.2514/1.J053318

  4. Ignatkin Yu.M., Konstantinov S.G. Trudy MAI, 2012, no. 57. URL: https://trudymai.ru/eng/published.php?ID=30875

  5. Vershkov V.A., Kritskii B.S., Makhnev M.S. et al. Trudy MAI, 2016, no. 89. URL: https://trudymai.ru/eng/published.php?ID=72704

  6. Ignatkin Yu.M., Makeev P.V., Shomov A.I. Trudy MAI, 2010, no. 38. URL: https://trudymai.ru/eng/published.php?ID=14148

  7. Ignatkin Yu.M., Makeev P.V., Shomov A.I. Trudy MAI, 2016, no. 87. URL: https://trudymai.ru/eng/published.php?ID=65636

  8. Animitsa V.A., Golovkin V.A., Nikol'skii A.A. Aerospace MAI Journal, 2020, vol. 27, no. 2, pp. 16-28.

  9. Nikol'skii A.A. Uchenye zapiski TsAGI, 2015, vol. 46, no. 8, pp. 30-41.

  10. Pavlenko N.S., Sypalo K.I., Kirillov O.E. et al. Polet, 2020, no. 4, pp. 10-18.

  11. Nikolsky A.A. About a geometric genotype of shapes of airfoils, Tsagi Science Journal, 2014, vol. 45, no. 5, pp. 417-429.

  12. Nikolsky A.A. Universal geometric transformation method PGT for aircraft design, 44th European rotorcraft forum, 2018, vol. 1, no, 40, pp. 456-467.

  13. Nikolsky A.A. Generalized inverse airfoil problem, Tsagi Science Journal, 2012, vol. 43, no. 6, pp. 775-786.

  14. Nikol'skii A.A. Trudy MAI, 2013, no. 88. URL: https://trudymai.ru/eng/published.php?ID=70417

  15. Wright A.H. Genetic Algorithms for Real Parameter, Foundations of Genetic algorithms I, 1990, pp. 205-218. DOI: 10.1016/B978-0-08-050684-5.50016-1

  16. Powell M.J.D. The BOBYQA algorithm for bound constrained optimization without derivatives, DAMTP, 2009, no. A 06, 39 p.

  17. Bauer F., Garabedian P., Korn D. Supercritical Wing Sections III, New York: Springer-Verlag, 1978, 184 p.

  18. Lyapunov S.V., Wolkov A.V. Numerical Prediction of Transonic Viscous Separated Flow Past an Airfoil, Theoretical and Computational Fluid Dynamics, 1994, vol. 6, no. 1, pp. 49-63.

  19. Programmnyi paket ANSYS Fluent. URL: http://www.ansys.com/Products/Fluids/ANSYS-Fluent

  20. Brenda K., Kulfan B., Bussoletti John E. "Fundamental" Parametric Geometry Representations for Aircraft Component Shapes, 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2006. DOI: 10.2514/6.2006-6948


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