Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-29T09:09:11.397Z Has data issue: false hasContentIssue false
  • English
  • Français

Influence of weight modelling on the outcome of wing design using multidisciplinary design optimisation techniques

Published online by Cambridge University Press:  27 January 2016

J. Mariens ,
A. Elham  and
M. J. L. van Tooren
J. Mariens
Affiliation:
Faculty of Aerospace Engineering, Delft University of Technology, The Netherlands
A. Elham*
Affiliation:
Faculty of Aerospace Engineering, Delft University of Technology, The Netherlands
M. J. L. van Tooren
Affiliation:
Faculty of Aerospace Engineering, Delft University of Technology, The Netherlands
*
[email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Weight estimation methods are categorised in different classes based on their level of fidelity. The lower class methods are based on statistical data, while higher class methods use physics based calculations. Statistical weight estimation methods are usually utilised in early design stages when the knowledge of designers about the new aircraft is limited. Higher class methods are applied in later design steps when the design is mature enough. Lower class methods are sometimes preferred in later design stages, even though the designers have enough knowledge about the design to use higher class methods. In high level multidisciplinary design optimisation (MDO) fidelity is often sacrificed to obtain models with shorter computation times. There is always a compromise required to select the proper weight estimation method for an MDO project.

An investigation has been performed to study the effect of using different weight estimation methods, with low and medium levels of fidelity, on the results of a wing design using multidisciplinary design optimisation techniques. An MDO problem was formulated to design the wing planform of a typical turboprop and a turbofan passenger aircraft. The aircraft maximum take-off weight was selected as the objective function. A quasi-three-dimensional aerodynamic solver was developed to calculate the wing aerodynamic characteristics. Five various statistical methods and a quasi-analytical method are used to estimate the wing structural weight. These methods are compared to each other by analysing their accuracy and sensitivity to different design variables. The results of the optimisations showed that the optimum wing shape is affected by the method used to estimate the wing weight. Using different weight estimation methods also strongly affects the optimisation convergence history and computational time.

Type
Research Article
Information
The Aeronautical Journal , Volume 117 , Issue 1195 , September 2013 , pp. 871 - 895
Copyright
Copyright © Royal Aeronautical Society 2013 

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

1. Jadic, I. A lifting line theory for supersonic flow applications, December 1991, Third AIAA International Aerospace Planes Conference, AIAA paper 91-5058, pp 1–10.Google Scholar
2. Haftka, R.T., Grossman, B., Eppard, W.M., Kao, P.J. and Polen, D.M. Efficient optimization of integrated aerodynamic-structural design, Int J for Numerical Methods in Engineering, 28, (3), 1989, pp 593–607.Google Scholar
3. Arian, E. and Vatsa, V.N. A preconditioning method for shape optimization governed by the Euler equations, Int J Computational Fluid Dynamics, 1999, 12, (1), pp 17–27.Google Scholar
4. Chiba, K., Obayashi, S. and Nakahashi, K. High-fidelity multidisciplinary design optimization of aerostructural wing shape for regional jet, June 2005, 23rd AIAA Applied Aerodynamics Conference, AIAA paper 2005-5080, pp 1–24.Google Scholar
5. Jameson, A., Martinelli, L. and Pierce, N. Optimum aerodynamic design using the Navier–Stokes equations, Theoretical and Computational Fluid Dynamics, 1998, 10, pp 213–237.Google Scholar
6. Elham, A. Structural design: weight estimation, Encyclopedia of Aerospace Engineering, June 2012, Blockley, R. and Shyy, W. (Eds), John Wiley: Chichester, UK.Google Scholar
7. Howe, D. Aircraft Conceptual Design Synthesis, 2000, Professional Engineering Publishing, London and Bury St Edmunds, UK.Google Scholar
8. Torenbeek, E. Synthesis of Subsonic Airplane Design, 1976, Delft University Press, Delft, The Netherlands.Google Scholar
9. Shevell, R.S. Fundamentals of Flight, 1983, Prentice-Hall, MI, USA.Google Scholar
10. Raymer, D.P. Aircraft Design: a Conceptual Approach, Fourth edition, 2006, AIAA (American Institute of Aeronautics and Astronautics) Education Series, Reston, VA, USA.Google Scholar
11. Torenbeek, E. Development and application of a comprehensive, design-sensitive weight prediction method for wing structures of transport category aircraft, September 1992, Report LR-693, Delft University of Technology, Delft, The Netherlands.Google Scholar
12. Macci, S.H. Semi-analytical method for predicting wing structural mass, May 1995, 54th Annual Conference, Society of Allied Weight Engineers, SAWE Paper 2282.Google Scholar
13. Elham, A., La Rocca, G. and van Tooren, M.J.L. Development and implementation of an advanced, design-sensitive method for wing weight estimation, Aerospace Science and Technology, 29, pp 100–113, 2013.Google Scholar
14. Bindolino, G., Ghiringhelli, G., Ricci, S. and Terraneo, M. Multilevel structural optimization for preliminary wing-box weight estimation, J Aircraft, March-April 2010, 47, (2).Google Scholar
15. Laban, M., Arendsen, P., Rouwhorst, W. and Vankan, W. Multidisciplinary design optimization for a blended wing body transport aircraft with distributed propulsion, September 2012, Ninth AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, AIAA paper 2001-5446, pp 1–11.Google Scholar
16. Obayashi, S. Multidisciplinary design optimization of aircraft wing planform based on evolutionary algorithms, October 1998, IEEE International Conference on Systems, Man, and Cybernetics, 4, pp 3148–3153.Google Scholar
17. Ursache, N.M., Melin, T., Isikveren, A.T. and Friswell, M.I. Morphing winglets for aircraft multi-phase improvement, September 2007, Seventh AIAA Aviation Technology, Integration and Operations Conference (ATIO), AIAA Paper 2007-7813, pp 1–12.Google Scholar
18. Bérard, A., Cavagna, L., Da Ronch, A., Riccobene, L., Ricci, S. and Isikveren, A. Development and validation of a next-generation conceptual aero-structural sizing suite, 2008, 26th International Congress of the Aeronautical Sciences, ICAS-2008-291, pp 1–10.Google Scholar
19. Isikveren, A. Quasi-analytical Modelling and Optimization Techniques for Transport Aircraft Design, May 2002, PhD thesis, Royal Institute of Technology (KTH), Stockholm, Sweden.Google Scholar
20. Torenbeek, E. Prediction of wing group weight for preliminary design, Aircraft Engineering and Aerospace Technology, July 1971, 43, (7), pp 16–21.Google Scholar
21. Torenbeek, E. Optimum wing area, aspect ratio and cruise altitude for long range transport aircraft, October 1994, Report LR-775, Delft University of Technology, Delft, The Netherlands.Google Scholar
22. Kroo, I. and Shevell, R. Aircraft Design: Synthesis and Analysis, Digital Textbook Version 1.2, September 2006, Desktop Aeronautics, Stanford, CA, USA, http://adg.stanford.edu/aa241/AircraftDesign.html,.Google Scholar
23. Howe, D. The prediction of aircraft wing mass, Proceedings Institution of Mechancial Engineers, Part G, J Aerospace Eng, 1996.Google Scholar
24. Dorbath, F. Large civil jet transport (MTOM > 40t) statistical mass estimation, 2011, DLR-LY/Airbus, LTH MA 401 12-01.+40t)+statistical+mass+estimation,+2011,+DLR-LY/Airbus,+LTH+MA+401+12-01.>Google Scholar
25. Obert, E., Slingerland, R., Leusink, D., van den Berg, T., Koning, J. and van Tooren, J. Aerodynamic Design of Transport Aircraft, 2009, IOS Press, Amsterdam, The Netherlands.Google Scholar
26. Martins, J.R. and Marriage, C. An object-oriented framework for multidisciplinary design optimization, April 2007, Third AIAA Multidisciplinary Design Optimization Specialist Conference, AIAA Paper 2007-1906, pp 1–15.Google Scholar
27. Cosyn, P. and Vierendeels, J. Numerical investigation of low-aspect-ratio wings at low Reynolds numbers, J Aircraft, 2006, 43, (3), pp 713–722.Google Scholar
28. Drela, M. and Youngren, H. AVL (Athena Vortex Lattice) 3.26, 2006, Massachusetts Institute of Technology, http://web.mit.edu/drela/Public/web/avl/.Google Scholar
29. Drela, M. and Youngren, H. XFOIL: Subsonic airfoil development system, Massachusetts Institute of Technology, http://web.mit.edu/drela/Public/web/xfoil/, Last accessed: June 2012.Google Scholar
30. Drela, M. MSES: Multi-element airfoil design/Analysis Software, Massachusetts Institute of Technology, http://raphael.mit.edu/drela/msessum.ps, Last accessed: June 2012.Google Scholar
31. Royal Aeronautical Society, VGK method for two-dimensional aerofoil sections (Part 1: principles and results), October 1996, Tech rep, ESDU (Engineering Sciences Data Unit) 96028.Google Scholar
32. Roskam, J. Airplane design: component weight estimation (Part V), Airplane Design, 1999, Design, Analysis and Research Corporation (DARcorporation), Lawrence, KS, USA.Google Scholar
33. Air BP Ltd, Handbook of products, http://www.bp.com/liveassets/bp_internet/aviation/air_bp/STAGING/local_assets/downloads_pdfs/a/air_bp_products_handbook_04004_1.pdf, Last accessed: June 2012.Google Scholar
34. Jenkinson, L., Rhodes, D. and Simpkin, P. Civil Jet Aircraft Design, 1999, AIAA education series, American Institute of Aeronautics and Astronautics.Google Scholar
35. Jenkinson, L., Rhodes, D. and Simpkin, P. Civil jet aircraft design — aircraft data set, http://www.elsevi-erdirect. com/companions/9780340741528/appendices/data-a/default.htm, Last accessed: June 2012.Google Scholar