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Identification of Volterra kernels for improved predictions of nonlinear aeroelastic vibration responses and flutter

机译:识别Volterra内核以改进非线性气动弹性振动响应和颤振的预测

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Aeroelastic structural systems are intrinsically nonlinear and accurate predictions of dynamic responses of nonlinear aeroelastic systems have become of paramount importance since these directly affect the accuracy and reliability of subsequent stability analyses. Such nonlinear systems can be generally represented with Volterra series whose kernels have been found to be effective in their dynamic characterizations. This paper examines how first- and second-order Volterra kernels of nonlinear aeroelastic systems can be accurately identified and then incorporated into the theoretical models of aeroelastic analyses such as predictions of dynamic response and onset of aeroelastic flutter. A novel identification method based on correlation analysis to extract frequency components has been developed which can be applied to general nonlinear aeroelastic systems to obtain accurately the required Volterra transfer functions. The method is very accurate and extremely robust against measurement noise contaminations in both input and output signals, due to the correlation scheme which effectively filters uncorrelated signal components. Detailed aeroelastic behavior of a representative pitch-plunge airfoil dynamic model with nonlinear pitch stiffness has been examined. Its Volterra transfer functions are then identified which are found to be close to their exact analytical counterparts, though interaction between kernels becomes apparent as input level increases. Once inverse Fourier transformed, these identified Volterra kernels are then included in the modeling of the dynamics of aeroelastic systems for vibration response and flutter. Extensive numerical simulation results have demonstrated that the proposed method is very accurate and resilient to measurement errors when applied to the identification of second-order Volterra kernels, and the improvement in predictions of vibration response and flutter become significant when the contributions of these second-order Volterra kernels are included in the overall aeroelastic system dynamics. The identification and subsequent inclusion of second-order Volterra kernels into system dynamics model offer improved design capabilities of nonlinear aeroelastic structural systems.
机译:气动弹性结构系统本质上是非线性的,非线性气动弹性系统动态响应的准确预测已变得至关重要,因为它们直接影响后续稳定性分析的准确性和可靠性。此类非线性系统通常可以用Volterra级数表示,该级数的内核已被证明在其动态表征方面有效。本文研究如何准确地识别非线性气动弹性系统的一阶和二阶Volterra核,然后将其纳入到气动弹性分析的理论模型中,例如动力学响应的预测和气动弹性颤振的发生。已开发出一种基于相关分析的提取频率分量的新颖识别方法,该方法可应用于一般的非线性气动弹性系统中,以准确获得所需的Volterra传递函数。由于有效地过滤了不相关信号分量的相关方案,该方法非常准确,并且对输入和输出信号中的测量噪声污染都非常鲁棒。研究了具有典型螺距刚度的典型螺距翼型动力学模型的详细气动弹性行为。然后,确定其Volterra传递函数,发现它们与精确的分析对应函数非常接近,尽管随着输入水平的增加,内核之间的交互作用变得明显。一旦进行了傅立叶逆变换,这些识别出的Volterra内核便被包括在气动弹性系统动力学建模中,以用于振动响应和颤动。大量的数值模拟结果表明,所提出的方法应用于二阶Volterra核的识别时,是非常准确且对测量误差具有弹性的,而当这些二阶贡献做出时,振动响应和颤动预测的改进就变得很重要。 Volterra内核包含在整个气动弹性系统动力学中。识别并随后将二阶Volterra内核包含到系统动力学模型中,可以改善非线性气动弹性结构系统的设计能力。

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