Reference : Data Clustering for the Identification of the Bifurcation Behaviour in Non-Linear Aeroel...
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Aerospace & aeronautics engineering
http://hdl.handle.net/2268/24462
Data Clustering for the Identification of the Bifurcation Behaviour in Non-Linear Aeroelastic Systems using a Coupled Harmonic Balance/Genetic Algorithm Approach
English
Vio, Gareth Arthur [University of Manchester > School of Mechanical Aerospace and Civil Engineering > > >]
Dimitriadis, Grigorios mailto [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 > > >]
Sep-2008
Proceedings of the 2008 International Conference on Noise and Vibration Engineering
Katholieke Universiteit Leuven
Paper ISMA2008-0009
No
No
International
978-90-7380-286-5
Heverlee
Belgium
2008 International Conference on Noise and Vibration Engineering
du 15 septembre au 17 septembre 2009
Katholieke Universiteit Leuven
Leuven
Belgium
[en] Data clustering ; Harmonic Balance ; Nonlinearity
[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.
Researchers ; Professionals
http://hdl.handle.net/2268/24462

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