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- W2006310978 abstract "Three approaches for reduced-order modeling of computational-fluid-dynamics-(CFD) based unsteady aerodynamics, employing system-identification methods, are presented, and used for generation of three models: A frequency-domain model, a time-domain autoregressive-moving-average model, and a discrete-time state-space model. All models are identified based on the same identification data, which consists of the time histories of the generalized aerodynamic forces developed in response to filtered white-Gaussian-noise modal excitation, computed in a CFD analysis. The models are used for rapid flutter analysis via traditional frequency-domain methods, linear stability analysis, and time simulation. The method is applied for flutter analysis of the AGARD 445.6 wing. The filtered white-Gaussian-noise input is found to be applicable within the framework of CFD, yielding informative identification data sets. The identification process is simple, and the resulting reduced-order models closely reproduce the CFD system response to various excitations. Reduced-order model-based flutter analysis is rapid and yields accurate results compared with wind-tunnel test, CFD, and linear aerodynamics results." @default.
- W2006310978 created "2016-06-24" @default.
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- W2006310978 date "2004-05-01" @default.
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- W2006310978 title "Identification of Computational-Fluid-Dynamics Based Unsteady Aerodynamic Models for Aeroelastic Analysis" @default.
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- W2006310978 doi "https://doi.org/10.2514/1.3149" @default.
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