An efficient strategy to incorporate designer-preferences in automated airfoil design

Carrese, R, Khurana, M, Winarto, H and Li, X 2011, 'An efficient strategy to incorporate designer-preferences in automated airfoil design', in Royal Aeronautical Society, Australian Division; Engineers Australia (ed.) Proceeding of the Fourteenth Australian International Aerospace Congress (AIAC14), Melbourne, Australia, 28 February - 3 March 2011, pp. 85-95.


Document type: Conference Paper
Collection: Conference Papers

Title An efficient strategy to incorporate designer-preferences in automated airfoil design
Author(s) Carrese, R
Khurana, M
Winarto, H
Li, X
Year 2011
Conference name The Fourteenth Australian International Aerospace Congress (AIAC14)
Conference location Melbourne, Australia
Conference dates 28 February - 3 March 2011
Proceedings title Proceeding of the Fourteenth Australian International Aerospace Congress (AIAC14)
Editor(s) Royal Aeronautical Society, Australian Division; Engineers Australia
Publisher Royal Aeronautical Society, Australian Division; Engineers Australia
Place of publication Melbourne, Australia
Start page 85
End page 95
Total pages 11
Abstract Multi-criteria aerodynamic design problems are not easily managed, and identifying all tradeoff solutions is often unnecessary and computational exhaustive. In this paper we propose a variant of a multi-objective particle swarm heuristic, which draws on the domain knowledge of the designer to obtain solutions of interest. The swarm is guided by a reference point situated on the objective landscape. This is viewed as an intuitive means of expressing the designer's preferred level of compromise, which can ideally be based on some existing or target design. An airfoil shape optimization case-study for a multi-mission spectrum is presented. A design space visualization tool known as self-organizing maps is introduced for post-optimization trade-off analyses. The explorative proficiency of the swarm, combined with the additional guidance provided by reference point, results in a final spread of trade-off designs which provide the most resemblance in compromise to the reference point.
Subjects Optimisation
Aerodynamics (excl. Hypersonic Aerodynamics)
Neural, Evolutionary and Fuzzy Computation
Keyword(s) Multi-objective optimization
airfoils
aerodynamics
particle swarms
designerpreferences
self-organizing maps.
Copyright notice © 2011 The Authors
ISBN 9780987086303
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