Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-22T10:00:26.929Z Has data issue: false hasContentIssue false

Shape optimisation using CAD linked free-form deformation

Published online by Cambridge University Press:  27 January 2016

A. Nurdin
Affiliation:
University of Southampton, Southampton, England, UK
N. W. Bressloff
Affiliation:
University of Southampton, Southampton, England, UK
A. J. Keane*
Affiliation:
University of Southampton, Southampton, England, UK
C. M. E. Holden
Affiliation:
Airbus Operations Limited, Bristol, England, UK

Abstract

Free-form deformation (FFD) is a method first introduced within the graphics industry to enable flexible deformation of geometric models. FFD uses an R3 to R3 mapping of a deformable space to the global Cartesian space to produce the geometry deformation. This method has been extensively used within the design optimisation field as a shape parameterisation technique. Typically it has been used to parameterise analysis meshes, where new design geometries are produced by deforming the original mesh. This method allows a concise set of design variables to be used while maintaining a flexible shape representation. However, if a computer aided design (CAD) model of the resulting geometry is required, reverse engineering techniques would need to be utilised to recreate the model from the deformed mesh. This paper extends the use of FFD within an optimisation routine by using FFD to directly parameterise a CAD geometry. Two methods of linking the FFD methods with the CATIA V5 CAD package are presented. Each CAD integration technique is then critiqued with respect to shape optimisation. Finally the set-up and initialisation of a case study is illustrated. The case study chosen is the aerodynamic optimisation of the wing-fuselage junction of a typical passenger aircraft.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2012 

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. Toal, D., Keane, A. and Bressloff, N. Kriging hyperparameter tuning strategies, AIAA J, May 2008, 46, (5), pp 12401252.Google Scholar
2. Samareh, J.A. Survey of shape parameterization techniques for high-fidelity multidisciplinary shape optimization, AIAA J, May 2001, 39, (5), pp 877884.Google Scholar
3. Sarakinos, S.S., Amoiralis, E. and Nikolos, I.K. Exploring freeform deformation capabilities in aerodynamic shape parameterization, 2005, EUROCON 2005 – International conference on ‘Computer as a Tool’, 1, pp 535538, November 2005, Belgrade, Serbia and Montenegro.Google Scholar
4. Andreoli, M., Janka, A. and Desideri, J. Free-form-deformation parameterization for multilevel 3D shape optimization in aerodynamics, November 2003, INRIA Research report 5019, Sophia Antipolis, France.Google Scholar
5. Sederberg, T.W. and Parry, S.R. Free-form deformation of solid geometric models, ACM SIGGRAPH Computer Graphics, August 1986, 20, (4), pp 151160.Google Scholar
6. Griessmair, J. and Purgathofer, W. Deformations of solids with trivariate B-spline, 1989, Eurographics conference, pp 2027, September 1989, North-Holland, Hamburg.Google Scholar
7. Lamousin, H.J. and Waggenspack, W.N. NURBS-based free-form deformations, IEEE Computer Graphics and Applications, November 1994, 14, (1), pp 5965.Google Scholar
8. Coquillart, S. Extended free-form deformation: a sculpturing tool for 3D geometric modeling, ACM SIGGRAPH Computer Graphics, August 1990, 24, (4), pp 187196.Google Scholar
9. Clark, J.H. Parametric curves, surfaces and volumes in computer graphics and computer-aided geometric design, 1981, Technical Report CSL-TR-81-221, Stanford University, Stanford, CA, USA.Google Scholar
10. Hsu, W.M., Hughes, J.F. and Kaufman, H. Direct manipulation of free-form deformations, Computer Graphics, July 1992, 26, (2), pp 177184.Google Scholar
11. Hu, S.-M., Zhang, H., Tai, C.-L. and Sun, J.-G. Direct manipulation of FFD: Efficient explicit solutions and decomposible multiple point constraints, The Visual Computer, July 2001, 17, (6), pp 370379.Google Scholar
12. Fudge, D.M., Zingg, D.W. and Haimes, R. A CAD-free and a CAD-based geometry control system for aerodynamic shape optimization, AIAA, January 2005, 51, (4), pp 115.Google Scholar
13. Menzel, S., Olhofer, M. and Sendhoff, B. Direct manipulation of free form deformation in evolutionary design optimisation, 2006, Parallel Problem Solving from Nature conference (PPSN IX), pp 352361, September 2006, Reykjavik, Iceland.Google Scholar
14. AIAA, Second drag prediction workshop, June 2003, http://aaac.larc.nasa.gov/tsab/cfdlarc/aiaa-dpw/Workshop2/, NASA, Orlando, FL, USA.Google Scholar
15. Raymer, D.P. Aircraft Design: A Conceptual Approach, Fourth edition, 2006, AIAA Education Series, p 159, New York, NY, USA.Google Scholar
16. Keane, A.J. The Options Design Exploration System Reference Manual and User GuideVersion B3. 1, 2005, University of Southampton, UK, http://www.soton.ac.uk/~ajk/options.ps, pp 10.110.8.Google Scholar
17. Voutchkov, I.I. and Keane, A.J. Multiobjective optimization using surrogates, 2006, Seventh International Conference on Adaptive Computing in Design and Manufacture, (ACDM 2006), pp 167175, May 2006, Bristol, UK.Google Scholar
18. Bardwell, R. Harpoon, 2007, http://www.sharc.co.uk/downloads/guidelines.pdf, Sharc, Manchester, UK.Google Scholar
19. Spalart, P.R. and Allmaras, S.R. A one equation turbulence model for aerodynamic flows, 1992, AIAA Paper 92-0439, 1, pp 521.Google Scholar
20. Rumsey, C., Rivers, S. and Morrison, J. Study of CFD variation on transport configurations from the second drag-prediction workshop, Computers and Fluids, August 2005, 34, (7), pp 785816.Google Scholar
21. Scheidegger, T. and Stuckert, G. DLR-F6 Wing-Body-Nacelle Simulations, June 2003, http://aaac.larc.nasa.gov/tsab/cfdlarc/aiaa-dpw/Workshop2/pdf/54Scheidegger_dpw2.pdf, NASA, Orlando, FL, USA.Google Scholar
22. Fonseca, C.M. and Fleming, P.J. An overview of evolutionary algorithms in multiobjective optimization, Evolutionary Computing, 3, pp 116, 1995.Google Scholar