Robust evolutionary algorithms for UAV/UCAV aerodynamic and RCS design optimisation

Computers and Fluids

Volumn 37, Issue 5, 2008, Pages 547-564

  Lee, D S ^a   Gonzalez, L F ^c   Srinivas, K ^a   Periaux, J ^b  

^a UNIVERSITY OF SYDNEY   (Australia)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^c QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AERODYNAMICS; AIRFOILS; EVOLUTIONARY ALGORITHMS; MANEUVERABILITY; OPTIMIZATION; RADAR CROSS SECTION;

AERODYNAMIC EFFICIENCY; AEROFOIL;

UNMANNED AERIAL VEHICLES (UAV);

AERODYNAMICS; AIRFOILS; EVOLUTIONARY ALGORITHMS; MANEUVERABILITY; OPTIMIZATION; RADAR CROSS SECTION; UNMANNED AERIAL VEHICLES (UAV);

EID: 40649104760     PISSN: 00457930     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compfluid.2007.07.008     Document Type: Article

References (27)

1. Wagner S, Sommerer A, Lutz T. Numerical optimisation of adaptive transonic airfoils with variable camber. In: Proceedings 22nd ICAS congress, no. ICA2.111, Harrogate, United Kingdom, August 27- September 1. Institute for Aerodynamics and Gas Dynamics, University of Stuttgart, Germany, p. 1-10.
2. Allison D, Sewall W. Airfoil modification effects on subsonic and transonic pressure distributions and performance for the EA-6B airplane. Technical report 3516, NASA, Hampton Virginia, May 1995.
3. Borer N. Design and analysis of low Reynolds number airfoils. Industrial math, Georgia Institute of Technology, December 2002.
4. Hansen N., and Ostermeier A. Completely derandomized self-adaptation in evolution strategies. Evolut Comput 9 2 (2001) 159-195
5. Koza J. Genetic programming II (1994), Massachusetts Institute of Technology
6. Quagliarella D, Vicini A. A multiobjective approach to transonic wing design by means of genetic algorithms. In: NATO RTO AVT symposium on aerodynamic design and optimization, no. RTO-MP-35, Ottawa, Canada, June 2000.
7. Chen S, Zhang F, Khalid M. Multi-point optimization of transonic wing by real-coded genetic algorithm. In: CFD2003, Vancouver, BC, May 28-30.
8. Zhang SCF, Khalid M. Multi-point optimization of transonic wing by real-coded genetic algorithm. In: CFD2003, Vancouver, BC, May 28-30.
9. Gano S, Renaud J. Optimized unmanned aerial vehicle with wing morphing for extended range and endurance. In: AIAA/ISSMO symposium and exhibit on multidisciplinary analysis and optimization, AIAA, vol. 9; 2002.
10. Mason W. Applied computational aerodynamics. page Appendix D: Programs, Tuesday, January 21, 1997.
11. Toivenen PJ. Evolutionary shape optimization in CFD with industrial applications. In: European congress on computational method in applied sciences and engineering (ECCOMAS), Barcelona, 11-14 September 2000.
12. Samli U, Cotuk N. Shaping considerations in the RCS reduction. In: AFCEA, 81504 Pendik Istanbul Turkey, 7-8 May 2003.
13. Stimon G. Introduction to airborne radar (1998), SciTech Publishing, Inc
14. Jameson A., Caughey D.A., Newman P.A., and Davis R.M. NYU transonic swept-wing computer program - FLO22 (1975), Langley Research Center
15. Lutz T. Airfoil design and optimisation. In: GAMM 2000 conference, Göttingen, Germany, April 2-7 2000.
16. Michalewicz Z. Genetic algorithms + data structures = evolution programs. Artificial intelligence (1992), Springer-Verlag
17. I, λ)-ES. EUFIT'97, 5th European Congress on Intelligent Techniques and Soft Computing, Proceedings, Aachen (1997), Verlag Mainz, Wissenschaftsverlag 650-654
18. Hansen N., Müller S.D., and Koumoutsakos P. Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). Evolut Comput 11 1 (2003) 1-18
19. Abbott I.H., and Doenhoff A.E.V. Theory of wing sections (1980), Dover
20. Srinivas K, Periaux J, Whitney EJ, Gonzalez LF, Sefrioui M. Adaptive evolution design without problem specific knowledge: UAV applications. In: Optimisation and control with application to industrial problems, EUROGEN, Barcelona, Spain, September 2003.
21. Gen M., and Cheng R. Genetic algorithm and engineering design. 1st ed. (1997), John Wiley and Sons, Inc., New York
22. Bolonkin A, Gilyard G. Estimated benefits of variable-geometry wing camber control for transport aircraft. Technical report TM-206586, NASA, October 1999.
23. Team deception, Department of Aeronautical & Astronautical Engineering at the University of Illinois. AIAA Undergraduate Design Competition 1998. http://www.aerospaceweb.org/design/ucav/.
24. Wakunda J, Zell A. Median-selection for parallel steady-state evolution strategies. In: PPSN, 2000. p. 405-14.
25. Lee DS, Gonzalez LF, Srinivas K, Auld DJ, Wong KC. Aerodynamic/RCS shape optimisation of unmanned aerial vehicles using hierarchical asynchronous parallel evolutionary algorithms. In: 25th applied aerodynamics conference, San Francisco, Hyatt Regency San Francisco at Embarcadero Center, CA, 5-8 June 2006.
26. Chatzigeorgiadis F., and Jenn D.C. A MATLAB physical-optics RCS prediction code. IEEE Antennas Propagat Mag 46 4 (2004) 136-139
27. Mason WH. Virginia Technology, Blacksburg, VA, Configuration aerodynamics. Appendix B: Fifteen minutes of stealth in aircraft design, French exhibit at the Montreal Expo, 1967. January 2006.