Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-24T07:39:50.599Z Has data issue: false hasContentIssue false
  • English
  • Français

Drag optimisation of a wing equipped with a morphing upper surface

Part of: Smart Aircraft

Published online by Cambridge University Press:  23 March 2016

A. Koreanschi ,
O. Sugar-Gabor  and
R. M. Botez
A. Koreanschi
Affiliation:
Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity LARCASE, ETS, University of Quebec, Montreal
O. Sugar-Gabor
Affiliation:
Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity LARCASE, ETS, University of Quebec, Montreal
R. M. Botez*
Affiliation:
Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity LARCASE, ETS, University of Quebec, Montreal
*
[email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The drag coefficient and the laminar-to-turbulent transition for the aerofoil component of a wing model are optimised using an adaptive upper surface with two actuation points. The effects of the new shaped aerofoils on the global drag coefficient of the wing model are also studied. The aerofoil was optimised with an ‘in-house’ genetic algorithm program coupled with a cubic spline aerofoil shape reconstruction and XFoil 6.96 open-source aerodynamic solver. The wing model analysis was performed with the open-source solver XFLR5 and the 3D Panel Method was used for the aerodynamic calculation. The results of the aerofoil optimisation indicate improvements of both the drag coefficient and transition delay of 2% to 4%. These improvements in the aerofoil characteristics affect the global drag of the wing model, reducing it by up to 2%. The analyses were conducted for a single Reynolds number and speed over a range of angles of attack. The same cases will also be used in the experimental testing of the manufactured morphing wing model.

Keywords

aerodynamicsmorphing wingsaerofoilstransitiondrag coefficient
Type
Research Article
Information
The Aeronautical Journal , Volume 120 , Issue 1225 , March 2016 , pp. 473 - 493
Copyright
Copyright © Royal Aeronautical Society 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Okamoto, N.D., Rhee, J., d Nikos, J. and Mourtos, N.J. Educating students to understand the impact of engineering solutions in a global/societal context, 8th UICEE Annual Conference on Engineering Education, 7-11 February 2005, Kingston, Jamaica.Google Scholar
2.Kwan, I. and Rutherford, D. U.S. Domestic Airline Fuel Efficiency Ranking, published 19 November 2014, http://www.theicct.org/us-domestic-airline-fuel-efficiency-ranking-2013, 2003.Google Scholar
3.United States Navy. F-14 Tomcat Fighter Fact File, 5 July 2003, retrieved 20 January 2007, cited January 2015.Google Scholar
4.Talay, Th. A.Introduction to the Aerodynamics of Flight, SP-367, 1975, Scientific and Technical Information Office, National Aeronautics and Space Administration, Washington, DC, US.Google Scholar
5.Bonnema, K. and Smith, S., AFTI/F-111 mission adaptive wing flight research program, AIAA Flight Test Conference, 1988, 4th ed, San Diego, California, US, pp 155–161.CrossRefGoogle Scholar
6.Smith, S.B. and Nelson, D.W.Determination of the aerodynamic characteristics of the mission adaptive wing, J of Airc, 1990, 27, (11), pp 950–958.CrossRefGoogle Scholar
7.Sofla, A.Y.N., Meguid, S.A., Tan, K.T. and Yeo, W.K.Shape morphing of aircraft wing: status and challenges, Materials & Design, 2010, 31, (3), pp 1284–1292.CrossRefGoogle Scholar
8.Barbarino, S., Bilgen, O., Ajaj, R.M., Friswell, M.I. and Inman, D.J.A review of morphing aircraft, J of Intelligent Material Systems and Structures, 2011, 22, (9), pp 823–877.CrossRefGoogle Scholar
9.Blondeau, J., Richeson, J., Darryll, J. and Pines, D.J.Design, development and testing of a morphing aspect ratio wing using an inflatable telescopic spar, AIAA Paper, 2003, 1718, pp 7–10.Google Scholar
10.Bharti, S., Frecker, M., Lesieutre, G. and Browne, J. Tendon actuated cellular mechanisms for morphing aircraft wing. The 14th International Symposium on: Smart Structures and Materials & Nondestructive Evaluation and Health Monitoring, April 2007, International Society for Optics and Photonics, pp 652307–652307. http://proceedings.spiedigitallibrary.orgCrossRefGoogle Scholar
11.Shili, L., Wenjie, G. and Shujun, L.Optimal design of compliant trailing edge for shape changing, Chinese J of Aeronautics, 2008, 21, (2), pp 187–192.CrossRefGoogle Scholar
12.Secanell, M., Suleman, A. and Gamboa, P. Design of a morphing airfoil for a light unmanned aerial vehicle using high-fidelity aerodynamic shape optimisation, 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Technical Paper AIAA 2005-1891, 2005, pp 1–20.CrossRefGoogle Scholar
13.Falcao, L., Gomes, A.A. and Suleman, A. Design and analysis of an adaptive wingtip, 52nd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Technical Paper AIAA 2011-2131, 4-7 April 2011, Denver, Colorado, US.CrossRefGoogle Scholar
14.Gamboa, P., Vale, J., Lau, F. J. P. and Suleman, A.Optimization of a morphing wing based on coupled aerodynamic and structural constraints, AIAA J, 2009, 47, (9), pp 2087–2104.CrossRefGoogle Scholar
15.Diodati, G., Ricci, S., De Gaspari, A., Huvelin, F., Dumont, A. and Godard, J.L. Estimated performance of an adaptive trailing-edge device aimed at reducing fuel consumption on a medium-sise aircraft, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2013, International Society for Optics and Photonics, Bellingham, Washington, US, pp 86900E-86900E.Google Scholar
16.Pecora, R., Amoroso, F. and Lecce, L.Effectiveness of wing twist morphing in roll control, J of Airc, 2012, 49, (6), pp 1667–1674.Google Scholar
17.Pecora, R., Francesco, A., Gianluca, A. and Concilio, A.Validation of a smart structural concept for wing-flap camber morphing, Smart Structures and Systems, 2014, 14, pp 659–678.Google Scholar
18.Pecora, R., Barbarino, S., Lecce, L. and Russo, S.Design and functional test of a morphing high-lift device for a regional aircraft, J of Intelligent Material Systems and Structures, 2011, 22, (10), pp 1005–1023.CrossRefGoogle Scholar
19.Sugar Gabor, O., Koreanschi, A. and Botez, R. M. Optimization of an Unmanned Aerial System'wing using a flexible skin morphing wing, Technical Paper SAE 2013-01-2095, 2013.CrossRefGoogle Scholar
20.Sugar Gabor, O., Simon, A., Koreanschi, A. and Botez, R.M. Application of a morphing wing technology on hydra technologies unmanned aerial system UAS-S4, ASME International Mechanical Engineering Congress and Exposition IMECE14, 14-20 November 2014, Montreal, Canada.Google Scholar
21.Sugar Gabor, O., Simon, A., Koreanschi, A. and Botez, R.M. Numerical optimization of the S4 Éhecatl UAS aerofoil using a morphing wing approach, American Institute of Aeronautics and Astronautics AIAA 32nd Applied Aerodynamics Conference, 16-20 June 2014, Atlanta, Georgia, US.Google Scholar
22.Sugar Gabor, O., Koreanschi, A. and Botez, R.M. Unmanned aerial system hydra technologies éhecatl wing optimization using a morphing approach, American Institute of Aeronautics and Astronautics AIAA Atmospheric Flight Mechanics Conference, 19-22 August 2013, Boston, Massachusetts, US.Google Scholar
23.Botez, R.M., Molaret, P. and Laurendeau, E. Laminar flow control on a research wing project presentation covering a three year period, 2007 AERO Conference and 54th Annual General Meeting, 2007 CASI Annual General Meeting, 2007, Toronto, Ontario, Canada.Google Scholar
24.Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M. and Mébarki, Y. A morphing wing used shape memory alloy actuators new control technique with Bi-positional and PI laws optimum combination - Part 1: Design phase, ICINCO 2010, Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics, 15-18 June 2010, Funchal, Madeira, Portugal.Google Scholar
25.Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M. and Mébarki, Y. A morphing wing used shape memory alloy actuators new control technique with bi-positional and PI laws optimum combination – Part 2: Experimental validation, ICINCO 2010, Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics, 15-18 June 2010, Funchal, Madeira, Portugal.Google Scholar
26.Coutu, D., Brailovski, V. and Terriault, P.Promising benefits of an active-extrados morphing laminar wing, J of Airc, 2009, 46, (2), pp 730–731.Google Scholar
27.Popov, A.V., Botez, R.M. and Labib, M.Transition point detection from the surface pressure distribution for controller design, J of Airc, 2008, 45, (1), pp 23–28.CrossRefGoogle Scholar
28.Silisteanu, P.D. and Botez, R.M. Two-dimensional aerofoil design for low speed aerofoils, AIAA Atmospheric Flight Mechanics Conference, Invited Session Paper, 2012, Minneapolis, Minnesota, US.Google Scholar
29.Courchesne, S., Popov, A.V. and Botez, R.M. New aeroelastic studies for a morphing wing, 48th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition, 2010, Orlando, Florida, US.CrossRefGoogle Scholar
30.Popov, A.V., Botez, R.M., Grigorie, T.L., Mamou, M. and Mebarki, Y.On–off and proportional–integral controller for a morphing wing part 1: Actuation mechanism and control design, J of Aerospace Engineering, 2012, 226, pp 131–145.Google Scholar
31.Popov, A.-V., Labib, M., Fays, J. and Botez, R.M.Closed loop control simulations on a morphing laminar using shape memory alloys actuators, AIAA J of Airc, 2008, 45, (5), pp 1794–1803.Google Scholar
32.Popov, A.V., Botez, R.M., Grigorie, T.L., Mamou, M. and Mebarki, Y.Real time aerofoil optimization of a morphing wing in wind tunnel, AIAA J of Aircr, 2010, 47, (4), pp 1346–1354.CrossRefGoogle Scholar
33.Grigorie, L.T. and Botez, R.M.Adaptive neuro-fuzzy inference system-based controllers for smart material actuator modelling, J of Aerospace Engineering, 2009, 223, (6), pp 655–668.Google Scholar
34.Grigorie, L.T., Botez, R.M. and Popov, A.V.Adaptive neuro-fuzzy controllers for an open loop morphing wing system, J of Aerospace Engineering, 2009, 223 (J), pp 965–975.Google Scholar
35.Drela, M. and Youngren, D.XFOIL Version 6.96 Documentation, 2001.Google Scholar
36.Drela, M.XFOIL: An analysis and design system for low Reynolds number airfoils, Low Reynolds Number Aerodynamics, 1989, Springer, Berlin, Heidelberg, Germany, pp 1–12.Google Scholar
37.Drela, M. Integral boundary layer formulation for blunt trailing edges, 7th Applied Aerodynamics Conference, Technical Paper AIAA 89-2166, 1989.Google Scholar
38.Drela, M. Implicit implementation of the full en transition criterion, Proceedings of 21st Applied Aerodynamics Conference, Technical Paper AIAA 2003-4066, 23-26 June 2003, Orlando, Florida, US.CrossRefGoogle Scholar
39.Mitchell, M.An introduction to genetic algorithms, A Bradford Book: An Introduction to Genetic Algorithms, 1996, MIT Press, Cambridge, Massachusetts, US.Google Scholar
40.Coley, D.A.An Introduction to Genetic Algorithms for Scientists and Engineers, 1999, World Scientific Publishing, Singapore.Google Scholar
41.Whitley, D.A genetic algorithm tutorial, Statistics and Computing, 1994, 4 (2), pp 65–85.Google Scholar
42.Sugar Gabor, O., Koreanschi, A. and Botez, R.M. Low - speed aerodynamic characteristics improvement of ATR 42 airfoil using a morphing wing approach, Proceedings of IECON 2012 – 38th Annual Conference of IEEE Industrial Electronics, 2012, Montreal, Quebec, Canada.Google Scholar
43.Abbott, I. and Doenhof, A.Theory of Wing Sections; Including a Summary of Airfoil Data, 1959, Dover Publications, Mineola, New York, US.Google Scholar
44.Kulfan, B.M. and Bussoletti, J.E. Fundamental parametric geometry representations for aircraft component shapes, Technical Paper AIAA 2006-6948, 2006.Google Scholar
45.Piegl, L. and Tiller, W.The NURBS Book. 2nd ed, 1997, Springer-Verlag, Berlin, Heidelberg, Germany.Google Scholar
46.Berbente, C., Mitran, S. and Zancu, S.Metode Numerice, 1997, Editura Tehnica, Bucharest, Romania, pp 12–16.Google Scholar
47.Online Redwoods college course http://online.redwoods.edu/instruct/darnold/LAPROJ/Fall98/SkyMeg/Proj.PDF, January 2014.Google Scholar
48.Herrera, F., Lozano, M. and Verdegay, J.L.Tackling real coded genetic algorithms: operators and tools for behavioural analysis, Artificial Intelligence Review, 1998, 12, (4), pp 265–319.Google Scholar
49.Fincham, J.H.S. and Friswell, M.I.Aerodynamic optimisation of a camber morphing aerofoil, Aerospace Science and Technology, 2015, 43, pp 245–255.Google Scholar
50.Deb, K. and Agrawal, R.B.Simulated binary crossover for continuous search space, Complex Systems, 1994, 9, (3), pp 1–15.Google Scholar
51.Deperrois, A. XFLR5 – Analysis of Foils and Wings Operating at Low Reynolds Numbers, XFLR5 manual and Guidelines, http://www.xflr5.com/xflr5.htm, February 2015.Google Scholar
52.Sivells, J.C. and Neely, R.H. Method for calculating wing characteristics by lifting line theory using nonlinear section lift data, NACA Technical Note, 1947, 1269.Google Scholar
53.Maskew, B. Program VSAERO theory document. NASA Contractor Report, 1987, 4023.Google Scholar
54.Katz, J. and Plotkin, A.Low Speed Aerodynamics. From Wing Theory to Panel Methods, 2nd ed, 2001, Cambridge University Press, Cambridge, UK.CrossRefGoogle Scholar