Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-25T09:01:16.264Z Has data issue: false hasContentIssue false
  • English
  • Français

Multi-disciplinary analysis and optimisation methodology for conceptual design of a box-wing aircraft

Published online by Cambridge University Press:  09 June 2016

Ishan Roy Salam  and
Cees Bil
Ishan Roy Salam*
Affiliation:
School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, Melbourne, Australia
Cees Bil
Affiliation:
School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, Melbourne, Australia
*
[email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper presents a multi-disciplinary analysis methodology for a box-wing aircraft configuration optimised for a given mission scenario. This conceptual design methodology and associated toolchain combines well-established vortex lattice analysis and a newly developed structural analysis tool called WingMASS, allowing the design space to be explored from a combined aerodynamics and structural design perspective. For a given mission scenario, the method optimises a box-wing configuration and compares it with an equivalent conventional configuration. This study shows that, for a given mission, a box-wing configuration can lead to a fuel burn reduction of up to 5% by optimising aspect ratio, horizontal and vertical wing separation.

Keywords

Aircraft designbox wingPrandtlPlaneconceptual designmulti-disciplinary analysis
Type
Research Article
Information
The Aeronautical Journal , Volume 120 , Issue 1230 , August 2016 , pp. 1315 - 1333
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. Cheze, B., Chevallier, J. and Gastineau, P. Forecasting world and regional air traffic in the mid-term (2025): An econometric analysis of air traffic determinants using dynamic panel-data models, 60e Congrès AFSE, 2011, Paris, France.CrossRefGoogle Scholar
2. Bows, A. Aviation and climate change: Confronting the challenge, Aeronautical J, 2010, 114, (1158), pp 459–466.CrossRefGoogle Scholar
3. Sgouridis, S., Bonnefoy, A. and Hansmann, R.J. Air transportation in a carbon constrained world: Long-term dynamics of policies and strategies for mitigating the carbon footprint of commercial aviation, Transportation Research Part A, 2011, 45, pp 1077–1091.Google Scholar
4. Nygren, E., Akelett, K. and Hook, M. Aviation fuel and future oil production scenarios, Energy Policy, 2009, 37, pp 4003–4010.CrossRefGoogle Scholar
5. ACARE Flightpath 2050: Europe's vision for aviation, Advisory Council for Aeronautics Research in Europe, 2011.Google Scholar
6. IATA A Global Approach to Reducing Aviation Emissions, International Air Transport Association, 2009.Google Scholar
7. Lee, D.S., Fahey, D.W., Forster, P.M., Newton, P.J., Wit, R.C.N., Lim, L.L., Owen, B. and Sausen, R. Aviation and global climate change in the 21st century, Atmospheric Environment, 2009, 43, pp 3520–3537.CrossRefGoogle Scholar
8. Koch, A., Lührs, B., Dahlmann, K., Linke, F., Grewe, V., Litz, M., Plohr, M., Nagel, B., Gollnick, V. and Schumann, U. Climate impact assessment of varying cruise flight altitudes applying the CATS simulation approach, 3rd International Conference of the European Aerospace Societies (CEAS), 2011, Venice, Italy.Google Scholar
9. Mistry, S., Smith, H. and Fielding, J.P. Development of novel aircraft concepts to reduce noise and global warming effects, 7th AIAA Technology, Integration and Operations Conference, 2011, Belfast.Google Scholar
10. Jansen, P.W. and Perez, R.E. Effect of size and mission requirements on the design optimization of non-planar aircraft configurations, 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference, 2010, Fort Worth, Texas, US.CrossRefGoogle Scholar
11. Prandtl, L. The induced drag of multiplanes, NACA TN-182, 1924.Google Scholar
12. Munk, M.M. General biplane theory, NACA TR-151, 1923.Google Scholar
13. Frediani, A. The prandtl wing, VKI Lecture Series: Innovative Configurations and Advanced Concepts for Future Civil Transport Aircraft, Von Karman Institute, June 2005.Google Scholar
14. Kroo, I. Drag due to lift: Concepts for prediction and reduction, Annual Review in Fluid Mechanics, 2001, 33, pp 587–617.CrossRefGoogle Scholar
15. Drela, M. and Youngren, H. AVL 3.26 User Primer, [Online] 29 April 2006, [Cited: 17 August 2014], http://web.mit.edu/drela/Public/web/avl/avl_doc.txt.Google Scholar
16. Genco, N. and Altman, A. Parametric study of the performance of a biplane joined at the tips, 47th AIAA Aerospace Sciences Meeting, 2009, Orlando, Florida, US.CrossRefGoogle Scholar
17. Melin, T. A Vortex Lattice MATLAB Implementation for Linear Aerodynamic Wing Applications, MSc Thesis, Royal Insitute of Technology (KTH), 2000.Google Scholar
18. Mamla, P. and Galinksi, C. Basic induced drag study of the joined-wing aircraft, J.Aircraft, 2009, 46, (4), pp 1438–1440.CrossRefGoogle Scholar
19. Landolfo, G. and Altman, A. Aerodynamic and structural design of a small nonplanar wing UAV, 47th AIAA Aerospace Sciences Meeting, 2009, Orlando, Florida, US.CrossRefGoogle Scholar
20. Garcia, G.E. and Becker, J. UAV stability derivatives estimation for hardware-in-the-loop simulation of Piccolo autopilot by qualitative flight testing, [Online] 2008, [Cited: 15 August 2015], http://www.aerodreams-uav.com/docs/aeroduav-conf.pdf.Google Scholar
21. Dorbath, F. A Flexible Wing Modeling and Physical Mass Estimation System for Early Aircraft Design Stages, PhD Thesis, German Aerospace Centre (DLR), 2014.Google Scholar
22. Dorbath, F., Nagel, B. and Gollnick, V. Extended physics-based wing mass estimation in early design stages applying automated model generation, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2013, pp 1-10.CrossRefGoogle Scholar
23. Raymer, D.P. Aircraft Design: A Conceptual Approach, 2012, AIAA, Washington, DC, US.CrossRefGoogle Scholar
24. Roskam, J. Airplane Design Part I: Preliminary Sizing of Aeroplanes, 2005, DAR Corp, Lawrence, Kansas, US.Google Scholar
25. Roskam, J. Airplane Design Part V: Component Weight Estimation, 2005, DAR Corp, Lawrence, Kansas, US.Google Scholar
26. Jemitola, P.O., Monterzino, G. and Fielding, J. Wing mass estimation algorithm for a medium range box wing aircraft, Aeronautical J, 2013, 117, (1183), pp 329–340.CrossRefGoogle Scholar
27. Byrnes, A.L., Hensleigh, W.E. and Tolve, L.A. Effect of horizontal stabilizer vertical location on the design of large transport aircraft, J. Aircraft, 1966, 3, (2), pp 97–104.CrossRefGoogle Scholar
28. Smith, S.C. and Stonum, R. K. Experimental aerodynamic characteristics of a joined-wing research aircraft configuration, NASA-TM-101083, 1989.Google Scholar