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.

老化的飞机或携带重型外部设备的运行飞机可能会在其飞行包线内表现出非线性气动弹性现象，例如极限循环振荡 (LCO)。一般来说，LCO 对飞机性能有负面影响，但由于非线性而导致的有限振幅 LCO 是比破坏性颤振振荡更好的替代方案。因此，对于飞行器设计以及主动和自适应控制的研究，检测非线性的存在非常重要。此外，找到非线性的特定类型也很重要。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，并预测不断变化的飞行条件下的气动弹性响应。所提出的方法结合了数学分析和统计方法。仅使用一组瞬态数据，这些方法就能够识别非线性并确定气动弹性系统的渐近状态。与气动弹性响应类似的振荡可以作为许多其他非线性动力系统的输出。因此，本项目不仅在非线性气动弹性研究方面具有强大的潜力，而且在非线性本质分析以及金融或生物医学复杂数据的预测方面也具有强大的潜力。