Tsing Ma bridge deck under skew winds—Part I: Aerodynamic coefficients

Zhu, Linbo; Xu, You Lin; Zhang, F.; He, Xiaoli

doi:10.1016/s0167-6105(02)00160-5

Cited by 38 publications

(6 citation statements)

References 3 publications

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“…As expected for such a sharp edged cross-section, the drag coefficient shows little dependence on u 0 , but decreases for increasing yaw angles, in agreement with the observations of Zhu et al (2002). The drag coefficient C d for the Lysefjord bridge deck was for design purposes set equal to 1.0, and its derivative equal to zero.…”

Section: Drag Coefficientsupporting

confidence: 86%

Full-scale observation of the flow downstream of a suspension bridge deck

Cheynet

Jakobsen

Snæbjörnsson

et al. 2017

Journal of Wind Engineering and Industrial Aerodynamics

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Section: Drag Coefficientsupporting

confidence: 86%

Full-scale observation of the flow downstream of a suspension bridge deck

Cheynet

Jakobsen

Snæbjörnsson

et al. 2017

Journal of Wind Engineering and Industrial Aerodynamics

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“…In the case of the Pescara footbridge the yaw angle θ approaches values of 54° close to the end. Experimental tests on the Tsing Ma Bridge (Zhu et al., a, b) showed that for a low reduced velocity, approximately

V^{*} < 8 \div 11

, the application of the skew wind theory provided results very close to experimental values. Also the so‐called “Wind Y” NSs of Table provided

V_{c r}

values always greater than that in NS A.…”

Section: Fe Model Updating According To the Skewed Wind Theory And Vamentioning

confidence: 83%

“…(), it is certainly more appropriate to define aerodynamic coefficients directly from wind‐tunnel tests (Zasso et al., ). The problem of deck curvature should also be considered, but the available literature is limited (Zhu et al., a,b).…”

Section: Introductionmentioning

confidence: 99%

Identification, Model Updating, and Validation of a Steel Twin Deck Curved Cable‐Stayed Footbridge

Bursi

Kumar

Abbiati

et al. 2014

Computer aided Civil Eng

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To perform a realistic reliability analysis of a complex cable‐stayed steel footbridge subject to natural hazard and corrosion, this article addresses a rational process of modeling and simulation based on identification, model updating, and validation. In particular, the object of this study is the Ponte del Mare footbridge located in Pescara, Italy; this bridge was selected as being a complex twin deck curved footbridge because it is prone to corrosion by the aggressive marine environment. With the modeling and simulation objectives in mind, a preliminary finite element (FE) model was realized using the ANSYS software. However, uncertainties in FE modeling and changes during its construction suggested the use of experimental system identification. As a result, the sensor location was supported by a preliminary FE model of the footbridge, although to discriminate close modes of the footbridge and locate identification sensor layouts, Auto Modal Assurance Criterion (AutoMAC) values and stabilization diagram techniques were adopted. Modal characteristics of the footbridge were extracted from signals produced by ambient vibration via the stochastic subspace identification (SSI) algorithm, although similar quantities were identified with free‐decay signals produced by impulse excitation using the ERA algorithm. All these procedures were implemented in the Structural Dynamic Identification Toolbox (SDIT) code developed in a MATLAB environment. The discrepancies between analytical and experimental frequencies led to a first update of the FE model based on Powell's dog‐leg method that relied on a trust‐region approach. As a result, the identified FE model was capable of reproducing the response of the footbridge subject to realistic gravity and wind load conditions. Finally, the FE was further updated in the modal domain, by changing both the stationary aerodynamic coefficients and the flutter derivatives of deck sections to take into account the effects of the curved deck layout.

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“…Brito and Riera introduced a peculiar experimental method to study how to sure static force coefficients in the condition of aeroelastic instability [37] . Based on sing Ma Bridge , six components coefficients of bridge deck of suspension bridge is determined by Zhu Ledong [38] . Tubino discussed the relationship of aerodynamic admittance function and flutter derivatives and static force coefficients [39] .…”

Section: The Significant and Status Of Aerodynamic Interferene Effectmentioning

confidence: 99%

Research status on aerodynamic interference effects of wind-resistant performance of pylon

Wang

et al. 2011

SPIE Proceedings

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The aerodynamic interference effects of wind-resistant performance for pylon is one of very important problems in numerical simulation studies of wind resistant of bridges. On the basis of looking through a great deal of related literatures at home and abroad, research history, contents, method and achievements of the aerodynamic interference effects are summarized, and the existing problem for galloping, buffeting and vortex-induced vibration of pylon and directions for the next research are pointed out.

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Tsing Ma bridge deck under skew winds—Part I: Aerodynamic coefficients

Cited by 38 publications

References 3 publications

Full-scale observation of the flow downstream of a suspension bridge deck

Full-scale observation of the flow downstream of a suspension bridge deck

Identification, Model Updating, and Validation of a Steel Twin Deck Curved Cable‐Stayed Footbridge

Research status on aerodynamic interference effects of wind-resistant performance of pylon

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