Buffeting response of long-span cable-supported bridges under skew winds. Part 1: theory

Zhu, Linbo; Xu, You Lin

doi:10.1016/j.jsv.2004.01.026

Cited by 58 publications

(21 citation statements)

References 32 publications

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“…These programs are now used to perform the structural internal force responses prediction of the Tsing Ma suspension Bridge with a main span of 1377m. The aerodynamic and aeroelastic parameters of bridge deck are taken from the wind tunnel test results (Zhu, 2002) and the reference mean wind speed is taken as 25m/s. The studied cases are listed in table 1.…”

Section: Random Vibration Methodsmentioning

confidence: 99%

TD3 Bridge3

Nietoa

Hernández

Jurado

et al. 2006

Wind Engineers, JAWE

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Optimization techniques are a very useful tool for engineers when dealing with the design of long span bridges. In this paper the formulation of the optimization problem considering aeroelastic constraints is shown. The optimum design process is a very much computer time demanding task, so distributed computing must be applied. Three examples of optimum design of the future Messina Strait Bridge are presented, where the thicknesses of the cross-sections of each box of the deck are adopted as design variables. It can be seen that very important material savings can be reached while satisfying the considered design constraints.

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Section: Random Vibration Methodsmentioning

confidence: 99%

TD3 Bridge3

Nietoa

Hernández

Jurado

et al. 2006

Wind Engineers, JAWE

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“…Equations (5)- (7) is expressed in a frequency manner for complex sinusoidal structural motions [33], but the self-excited forces can be reshaped as aerodynamic stiffness and aerodynamic damping [6,9,34,35]. Hence, the governing equation by Equation (1) can be further expressed as …”

Section: H(t)mentioning

confidence: 99%

“…In this study, this number will be odd considering the distribution in Figure 13a. The relationship between N and subscript n can be expressed as Equation (9). When the other parameters are given, more TMDs will lead to more intensive natural frequencies.…”

Section: Design Parameters Of the Mtmdmentioning

confidence: 99%

Parametric Sensitivity Analysis on the Buffeting Control of a Long-Span Triple-Tower Suspension Bridge with MTMD

et al. 2017

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Abstract:The long-span triple-tower suspension bridge is a brand-new type of structural form with typical wind-sensitive features. Inevitable wind-induced vibrations will heavily influence the driving comfort during strong winds and shorten the fatigue life of the bridge structure, which highlights the demand for the mitigation of wind-induced vibrations of long-span bridges. In this study, a parametric analysis is performed to investigate the control effect of multiple tuned mass dampers (MTMD) on the buffeting responses of a long-span triple-tower suspension bridge. Taking Taizhou Bridge as an example, the buffeting analysis is conducted via the finite-element-based approach. A step-updating framework is presented to guide the parametric analysis and determine the preferred values of the mechanical parameters of the MTMD. Specifically, four parameters-including the number of TMDs, the mass ratio, the damping ratio, and the frequency bandwidth ratio-are included in the parametric analysis. The robustness of the MTMD is also evaluated by changing another parameter called the frequency ratio. It is found that the performance of the MTMD is sensitive to the variation of the four parameters and the robustness can be adjusted by increasing the frequency bandwidth ratio. Utilizing the MTMD with reasonable mechanical parameters, the buffeting responses of the long-span triple-tower suspension bridge under strong winds can be effectively mitigated.

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“…Therefore, it is necessary to take into account the mechanical nonlinear behaviors when studying aerodynamic or aeroelastic performances of bluff bodies via SSSM tests, because the aerodynamic and aeroelastic parameters used in the research are commonly identified through identification of system parameters and by subtracting the mechanical damping and stiffness obtained in the still air condition from the overall ones identified under the flowing air (i.e. wind) conditions [1,[5][6][7][8]. Therefore, neglecting mechanical nonlinearities will undoubtedly introduce the modeling errors of mechanical damping and stiffness into the identification results of aerodynamic parameters, which is likely one of the main causes of frequent dispersion of identified flutter derivates at high reduced wind speed [2,5], where large initial excitations are needed to get long-duration signals of free decay vibrations.…”

Section: Introductionmentioning

confidence: 99%