期刊
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS
卷 214, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.jweia.2021.104650
关键词
Nonlinear flutter derivatives; Unscented Kalman filter; Bridge deck; Vortex-induced vibration; Flutter; Buffeting response; Parameter identification
资金
- NSF [CMMI1536108]
This study proposes an unscented Kalman filter approach for identifying linear or nonlinear flutter derivatives of bridge decks, with a focus on torsional vibration amplitudes and polynomial representations. The method is capable of simultaneously estimating the augmented state variables of the two degrees of freedom bridge deck system. It also demonstrates the successful extraction of nonlinear FDs and reveals the limitations of linear models, while examining the identification of unknown buffeting force excitations.
This study presents an unscented Kalman filter (UKF) approach for identification of linear or nonlinear flutter derivatives (FDs) of bridge decks from free vibration or buffeting response time history. The nonlinear FDs, which are dependent on torsional vibration amplitude, are represented in polynomial functions of torsional displacement. The augmented state variables of the two degrees of freedom (2DOF) bridge deck system, which include bridge deck motions and unknown FDs, are estimated simultaneously with the UKF approach based on response measurement data. Firstly, the steady-state vortex-induced vibration and flutter of a streamlined bridge deck section are used to illustrate the performance of UKF approach in extracting nonlinear FDs. The equivalent linear FDs are also identified from the same response data which reveals the deficiency of the linear model. Secondly, the stochastic buffeting responses of the bridge deck contributed from two modal responses with linear FDs are generated, and the performance of UKF approach with unknown excitations is examined. It is pointed out that the buffeting response must be separated into two modal response components, such that the unknown buffeting force excitations identification of FDs.
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