Identification of Flutter Derivatives of Bridge Decks in Wind Tunnel Test by Stochastic Subspace Identification
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Copyright: © 2020 T. Janesupasaeree and V. Boonyapinyo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.
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- Flutter derivatives
- covariance-driven stochastic subspace identification
- wind tunnel test
- bridge decks
- turbulent flow