Robust aerodynamic design optimisation of morphing aerofoil/wing using distributed moga


Autoria(s): Lee, D.S.; Gonzalez, Luis F.; Periaux, J; Onate, E
Contribuinte(s)

Grant, I

Data(s)

2012

Resumo

In this paper, the shape design optimisation using morphing aerofoil/wing techniques, namely the leading and/or trailing edge deformation of a natural laminar flow RAE 5243 aerofoil is investigated to reduce transonic drag without taking into account of the piezo actuator mechanism. Two applications using a Multi-Objective Genetic Algorithm (MOGA)coupled with Euler and boundary analyser (MSES) are considered: the first example minimises the total drag with a lift constraint by optimising both the trailing edge actuator position and trailing edge deformation angle at a constant transonic Mach number (M! = 0.75)and boundary layer transition position (xtr = 45%c). The second example consists of finding reliable designs that produce lower mean total drag (μCd) and drag sensitivity ("Cd) at different uncertainty flight conditions based on statistical information. Numerical results illustrate how the solution quality in terms of mean drag and its sensitivity can be improved using MOGA software coupled with a robust design approach taking account of uncertainties (lift and boundary transition positions) and also how transonic flow over aerofoil/wing can be controlled to the best advantage using morphing techniques.

Identificador

http://eprints.qut.edu.au/60081/

Publicador

Optimage Ltd, on behalf of the International Council of the Aeronautical Sciences (ICAS).

Relação

http://www.icas.org/ICAS_ARCHIVE/ICAS2012/ABSTRACTS/154.HTM

Lee, D.S., Gonzalez, Luis F., Periaux, J, & Onate, E (2012) Robust aerodynamic design optimisation of morphing aerofoil/wing using distributed moga. In Grant, I (Ed.) Proceedings of the 28th Congress of the International Council of the Aeronautical Sciences, Optimage Ltd, on behalf of the International Council of the Aeronautical Sciences (ICAS). , Brisbane, Qld.

Direitos

Copyright 2012 please consult the authors

Fonte

Australian Research Centre for Aerospace Automation; School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #Robust/uncertainty design #Multi-objective genetic algorithms (moga) #Parallel computing #Morphing wing
Tipo

Conference Paper