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- W2313002410 abstract "Three approaches for reduced order modeling of linearized unsteady aerodynamics, based on well-established system identification methods, are presented, and used for generation of three models: A frequency domain model, a time- domain ARMA 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.
- W2313002410 created "2016-06-24" @default.
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- W2313002410 date "2003-04-07" @default.
- W2313002410 modified "2023-09-25" @default.
- W2313002410 title "Identification of CFD-Based Unsteady Aerodynamic Models for Aeroelastic Analysis" @default.
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- W2313002410 doi "https://doi.org/10.2514/6.2003-1407" @default.
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