Analyzing and predicting the nonlinear aeroelastic response

分析和预测非线性气动弹性响应

• 批准号: 327615-2006
• 负责人: Popescu, Cristina
• 金额: $ 0.44万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=397869
• 关键词: Analyzing; predicting; nonlinear; aeroelastic; response

Aging aircraft or operational aircraft carrying heavy externals may exhibit nonlinear aeroelastic phenomena, such as limit cycle oscillations (LCO), within their flight envelope. Generally the LCO has a negative effect on the aircraft performance, but limited amplitude LCOs due to non-linearities, are a better alternative than the onset of destructive flutter oscillations. Thus, for the flight vehicle design, and in the study of active and adaptive control, it is important to detect the presence of the non-linearities. Moreover, finding the particular type of the non-linearities is also important. The main objective of this project is to develop methods for detecting the nonlinearities associated with an aeroelastic system, and to predict the aeroelastic response for changing flight conditions. The proposed methodology incorporates mathematical analysis and statistical methods. Using only a set of transient data, these methods are capable of identifying nonlinearities and determining the asymptotic state of the aeroelastic system. Oscillations similar with the aeroelastic response can be found as the output of many other nonlinear dynamical systems. Thus, the present project has a strong potential not only in the study of nonlinear aeroelasticity, but also in the analysis of the nature of nonlinearities and in the prediction of financial or biomedical complex data.

老龄飞机或携带重型外部部件的现役飞机在其飞行包线内可能会表现出非线性气动弹性现象，如极限环振荡（LCO）。一般来说，LCO对飞机性能有负面影响，但由于非线性，有限振幅的LCO比破坏性颤振振荡的开始是一个更好的选择。因此，对于飞行器的设计，以及在主动和自适应控制的研究中，检测非线性的存在是重要的。此外，找到特定类型的非线性也很重要。该项目的主要目标是开发检测与气动弹性系统相关的非线性的方法，并预测飞行条件变化时的气动弹性响应。所提出的方法结合了数学分析和统计方法。这些方法仅使用一组瞬态数据，就能够识别气动弹性系统的非线性并确定其渐近状态。类似于气动弹性响应的振荡可以作为许多其他非线性动力系统的输出而被发现。因此，本项目不仅在非线性气动弹性研究中，而且在非线性性质的分析和金融或生物医学复杂数据的预测中具有很强的潜力。