Please use this identifier to cite or link to this item: https://doi.org/10.2514/6.2013-1863
Title: Reduced-order aeroelastic modeling using coupled CFD-CSD simulations and system identification technique
Authors: Lai, K.L. 
Kim, T.
Issue Date: 2013
Citation: Lai, K.L.,Kim, T. (2013). Reduced-order aeroelastic modeling using coupled CFD-CSD simulations and system identification technique. 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. ScholarBank@NUS Repository. https://doi.org/10.2514/6.2013-1863
Abstract: A aeroelastic reduced-order modeling (ROM) technique based on the coupled fluid-structure aeroelastic response with a reduced set of state variables is presented in this paper. Assuming that the structural model is known a priori from a structural dynamics analysis and using linear transformations between structural and aeroelastic states, it is possible to identify the underlying aerodynamic system from the sampled time histories of the aeroelastic system. Once the aerodynamic model is known, an aeroelastic reduced-order model can be constructed in discrete-time, state-space format by coupling the structural model and the aerodynamic system. An advantange of the present method is that it works directly on time-history data of the coupled aeroelastic system, making it possible to utilize data from both experimental measurements and numerical simulations. The present reduced-order model is suitable for constant Mach, varying density (CMVD) analysis including flutter prediction and dynamic response calculation. For application and verification of the method the AGARD 445.6 wing will be considered. Computational aeroelasticity will be used for calculating aeroelastic responses. Flutter boundaries predicted by the reduced-order models will be compared to published test results for various Mach conditions. © 2013 by Lai Kwok Leung.
Source Title: 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/116772
ISBN: 9781624102233
DOI: 10.2514/6.2013-1863
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