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首页> 外文期刊>American journal of engineering and applied sciences >Identification of Flutter Derivatives of Bridge Decks in Wind Tunnel Test by Stochastic Subspace Identification | Science Publications
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Identification of Flutter Derivatives of Bridge Decks in Wind Tunnel Test by Stochastic Subspace Identification | Science Publications

机译:随机子空间识别的风洞试验中桥架颤振派生识别科学出版物

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> Problem statement: Flutter derivatives are the essential parameters in the estimations of the flutter critical wind velocity and the responses of long-span cable supported bridges. These derivatives can be experimentally estimated from wind tunnel test results. Generally, wind tunnel test methods can be divided into free decay test and buffeting test. Compared with the free decay method, the buffeting test is simpler but its outputs appear random-like. This makes the flutter derivatives extraction from its outputs more difficult and then a more advanced system identification is required. Most of previous studies have used deterministic system identification techniques, in which buffeting forces and responses are considered as noises. These previous techniques were applicable only to the free decay method. They also confronted some difficulties in extracting flutter derivatives at high wind speeds and under turbulence flow cases where the buffeting responses dominate. Approach: In this study, the covariance-driven stochastic subspace identification technique (SSI-COV) was presented to extract the flutter derivatives of bridge decks from the buffeting test results. An advantage of this method is that it considers the buffeting forces and responses as inputs rather than as noises. Numerical simulations and wind tunnel tests of a streamlined thin plate model conducted under smooth flow by the free decay and the buffeting tests were used to validate the applicability of the SSI-COV method. Then, wind tunnel tests of a two-edge girder blunt type of Industrial-Ring-Road Bridge deck (IRR) were conducted under smooth and turbulence flow. Results: The identified flutter derivatives of the thin plate model by the SSI-COV technique agree well with those obtained theoretically. The results from the thin plate and the IRR Bridge deck validated the reliability and applicability of the SSI-COV technique to various experimental methods and conditions of wind flow. Conclusion/Recommendations: The SSI-COV was successfully employed to identify flutter derivatives of bridge decks with reliable results. It is a proven technique that can be readily applied to identify flutter derivatives of other bridge decks either by the free decay or the buffeting tests.
机译: > 问题陈述:颤振导数是估算颤振临界风速和大跨度斜拉桥的响应时必不可少的参数。这些导数可以通过风洞测试结果进行实验估算。通常,风洞测试方法可以分为自由衰减测试和抖振测试。与自由衰减方法相比,抖振测试更简单,但其输出看起来像随机的。这使得从其输出提取颤动导数更加困难,然后需要更高级的系统识别。先前的大多数研究都使用确定性系统识别技术,其中抖振力和响应被视为噪声。这些先前的技术仅适用于自由衰减方法。他们还面临着一些困难,即在高风速下以及在抖振响应占主导的湍流情况下提取颤振导数。 方法:在这项研究中,提出了用协方差驱动的随机子空间识别技术(SSI-COV)从抖振测试结果中提取桥面板的颤振导数。该方法的优点在于,将抖振力和响应视为输入而不是噪声。数值模拟和流线型薄板模型的风洞试验通过自由衰减和抖振试验在光滑流动下进行,以验证SSI-COV方法的适用性。然后,在光滑和湍流的条件下,对工业环行路桥甲板(IRR)的两边大梁钝型风洞进行了试验。结果:已识别的薄板模型颤动导数通过SSI-COV技术获得的结果与理论上获得的结果非常吻合。薄板和IRR桥面的结果验证了SSI-COV技术在各种实验方法和风流条件下的可靠性和适用性。 结论/建议: SSI-COV已成功用于识别桥面板的颤振导数,结果可靠。这是一种经过验证的技术,可以通过自由衰减或抖振测试轻松地应用于识别其他桥面板的颤振导数。

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