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Direct identification of flutter derivatives and aerodynamic admittances of bridge decks

机译:直接识别桥面颤振导数和空气动力学导纳

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摘要

Flutter derivatives and aerodynamic admittances provide basis of predicting the critical wind speed in flutter and buffeting analysis of long-span cable-supported bridges. In this paper, one popular stochastic system identification technique, covariance-driven stochastic subspace identification (SSI in short), is first presented for estimation of the flutter derivatives and aerodynamic admittances of bridge decks from their random responses in turbulent flow. Numerical simulations of an ideal thin plate are adopted to extract these aerodynamic parameters to evaluate the applicability of the present method. Then wind tunnel tests of a streamlined thin plate model and a Π type blunt bridge section model were conducted in turbulent flow and the flutter derivatives and aerodynamic admittances are determined by the SSI technique. The identified aerodynamic parameters are compared with the theoretical ones and the results indicate the applicability of the current method.
机译:颤振导数和空气动力学导纳为预测大跨度斜拉桥在颤振和抖振分析中的临界风速提供了基础。在本文中,首先提出了一种流行的随机系统识别技术,即协方差驱动的随机子空间识别(简称SSI),用于根据湍流中桥面板的颤振导数和空气动力学导纳来评估其随机响应。采用理想薄板的数值模拟来提取这些空气动力学参数,以评估本方法的适用性。然后在湍流中进行了流线型薄板模型和Π型钝桥截面模型的风洞试验,并通过SSI技术确定了颤振导数和空气动力学导纳。将确定的空气动力学参数与理论参数进行比较,结果表明了当前方法的适用性。

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