Abstract
A practical three-dimensional shape optimization for aerodynamic design of a transonic wing has been performed using Evolutionary Algorithms (EAs). Because EAs coupled with aerodynamic function evaluations require enormous computational time, Numerical Wind Tunnel (NWT) located at National Aerospace Laboratory in Japan has been utilized based on the simple master-slave concept. Parallel processing makes EAs a very promising approach for practical aerodynamic design.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, third revised edition, Springer-Verlag, (1996).
Janikow, C. Z. and Michalewicz, Z., An Experimental Comparison of Binary and Floating Point Representations in Genetic Algorithms, Proc. of the 4th Intl. Conference on Genetic Algorithms, (1991), pp.31–36.
Arakawa, M. and Hagiwara, I., Development of Adaptive Real Range (ARRange) Genetic Algorithms, JSME Intl. J., Series C, Vol. 41, No. 4 (1998), pp. 969–977.
Arakawa, M. and Hagiwara, I., Nonlinear Integer, Discrete and Continuous Optimization Using Adaptive Range Genetic Algorithms, Proc. of 1997 ASME Design Engineering Technical Conferences, (1997).
Krishnakumar, K., Swaminathan, R., Garg, S. and Narayanaswamy, S., Solving Large Parameter Optimization Problems Using Genetic Algorithms, Proc. of the Guidance, Navigation, and Control Conference, (1995), pp.449–460.
Mulgund, S., Harper, K., Krishnakumar, K. and Zacharias. G., Air Combat Tactics Optimization Using Stochastic Genetic Algorithms, Proc. of 1998 IEEE Intl. Conference on Systems, Man, and Cybernetics, (1998), pp.3136–3141.
Baker, J. E., Reducing Bias and Inefficiency in the Selection Algorithm, Proc. of the 2nd Intl. Conference on Genetic Algorithms, (1987), pp.14–21.
Oyama, A., Obayashi, S. and Nakahashi, K., Wing Design Using Real-Coded Adaptive Range Genetic Algorithm, Proc. of 1999 IEEE Intl. Conference on Systems, Man, and Cybernetics [CD-ROM], (1999).
Obayashi, S. and Guruswamy, G. P., “Convergence Acceleration of an Aeroelastic Navier-Stokes Solver,” AIAA Journal, Vol. 33, No. 6, 1995, pp.1134–1141.
Case, J., Chilver, A. H. and Ross, C. T. F., Strength of Materials & Structures with an Introduction to Finite Element Methods, 3rd Edn., Edward Arnold, London, 1993.
Sobieczky, H, Parametric Airfoils and Wings, Recent Development of Aerodynamic Design Methodologies-Inverse Design and Optimization, Friedr. Vieweg & Sohn Verlagsgesellschaft mbH, Braunschweig/Wiesbaden, (1999), pp.72–74.
Oyama, A., Obayashi, S., Nakahashi, K. and Hirose, N., Fractional Factorial Design of Genetic Coding for Aerodynamic Optimization, AIAA Paper 99-3298, (1999).
Nakamura, T., Iwamiya, T., Yoshida, M., Matsuo, Y. and Fukuda, M., Simulation of the 3 Dimensional Cascade Flow with Numerical Wind Tunnel (NWT), Proc. of the 1996 ACM/IEEE Supercomputing Conference [CD-ROM], (1996).
Harris, C. D., NASA Supercritical Airfoils, NASA TP 2969, (1990).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Obayashi, S., Oyama, A., Nakamura, T. (2000). Transonic Wing Shape Optimization Based on Evolutionary Algorithms. In: Valero, M., Joe, K., Kitsuregawa, M., Tanaka, H. (eds) High Performance Computing. ISHPC 2000. Lecture Notes in Computer Science, vol 1940. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39999-2_15
Download citation
DOI: https://doi.org/10.1007/3-540-39999-2_15
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41128-4
Online ISBN: 978-3-540-39999-5
eBook Packages: Springer Book Archive