ORBi: Vio Gareth Arthur - Data Clustering for the Identification of the Bifurcation Behaviour in Non-Linear Aeroelastic Systems using a Coupled Harmonic Balance/Genetic Algorithm Approach

Reference : Data Clustering for the Identification of the Bifurcation Behaviour in Non-Linear Aeroel...


	Document type :	Scientific congresses and symposiums : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Aerospace & aeronautics engineering
	To cite this reference:	http://hdl.handle.net/2268/24462

Title :	Data Clustering for the Identification of the Bifurcation Behaviour in Non-Linear Aeroelastic Systems using a Coupled Harmonic Balance/Genetic Algorithm Approach
Language :	English
Author, co-author :	Vio, Gareth Arthur [University of Manchester > School of Mechanical Aerospace and Civil Engineering > > >]
	Dimitriadis, Grigorios [Université de Liège - ULg > Département d'aérospatiale et mécanique > Interactions Fluide-Structure - Aérodynamique expérimentale >]
	Cooper, Jonathan Edward [University of Manchester > School of Mechanical Aerospace and Civil Engineering > > >]
Publication date :	Sep-2008
Main document title :	Proceedings of the 2008 International Conference on Noise and Vibration Engineering
Publisher :	Katholieke Universiteit Leuven
Pages :	Paper ISMA2008-0009
On invitation :	No
Audience :	International
ISBN :	978-90-7380-286-5
City :	Heverlee
Country :	Belgium
Event name :	2008 International Conference on Noise and Vibration Engineering
Event date :	du 15 septembre au 17 septembre 2009
Event organizer :	Katholieke Universiteit Leuven
Event place (city) :	Leuven
Event country :	Belgium
Keywords :	[en] Data clustering ; Harmonic Balance ; Nonlinearity
Abstract :	[en] This paper describes an efficient method for calculating the bifurcation behaviour of an aeroelastic system using a Harmonic Balance expansion coupled with a Genetic Algorithm, combined with a clustering algorithm in order to determine all the solutions at every single flight condition. It will be shown how it is possible to obtain all the bifurcation branches in one step. Two clustering algorithms, K-Means and PAM, together with a number of cluster index techniques, such as Davies-Boulding, Calinski-Harabasz are investigated. The method is applied to an aeroelastic galloping problem as this phenomenon presents a number of co-existing limit cycles at a range of airspeeds.
Target :	Researchers ; Professionals
Permalink :	http://hdl.handle.net/2268/24462

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