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System identification and signal processing for nonlinear aeroelastic systems

System identification and signal processing for nonlinear aeroelastic systems
非线性气动弹性系统的系统辨识和信号处理
批准号:
387042-2010
负责人:
Marsden, Catharine
金额:
$1.53万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2010
资助国家:
加拿大
项目状态:
已结题
起止时间:
2010-01-01 至 2011-12-31

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英文摘要
The objective of this research program is to develop and validate, both numerically and experimentally, a set of analytical tools for the identification and characterization of nonlinear aeroelastic systems, with a specific focus on globally linear systems containing isolated nonlinearities. The tools will be time, frequency and time-frequency based and will be used to 1) identify nonlinear aeroelastic systems from non-critical test data, 2) characterize aeroelastic nonlinearities and 3) extract linear and nonlinear system parameters in order to predict transient, uncertain and unstable behaviours such as limit cycle oscillations and chaos. The research program combines numerical modeling, experimental and analytical approaches to modal testing and signal processing for nonlinear aeroelastic systems. A numerical model is developed that can simulate the free- and forced-response of a structurally linear or nonlinear, two or three degree-of-freedom, rigid airfoil section. The numerical model is validated against wind tunnel test data and employed to generate data for nonlinear aeroelastic response over a range of airfoil configurations and for several distinct structurally nonlinear parameters. Data obtained from simulations will be used to design and expand the wind tunnel test-section capability as well as develop signal processing tools based on classical Fourier analysis, reverse input/output analysis, restoring force surfaces, spectrographs, and other signal processing techniques. These tools will be adapted to the nonlinear aeroelastic environment and used to extract system parameter information associated with the systems uniquely nonlinear behaviour, and with the transition from stable to unstable aeroelastic behaviour. The ouput from the different tools will be combined to map the evolution of the system parameters, and studied for patterns and identifying features that will enable the prediction of instabilities. Predictive results will be validated with numerical simulations and wind tunnel tests. The results of this research are expected to contribute significant value to the engineering community dealing with instabilities of nonlinear aeroelastic and fluid/structure systems.
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