Reaction Spectrum Comparative Analysis of Seismic Performance of 62 m CFST Bridge with Curved-String Truss before and after Reinforcement

Taking a 62 m CFST bridge with a curved-string truss as the research object, according to its reinforcement scheme, the spatial finite element models of the bridge before and after reinforcement were established by using the general finite element software ANSYS. The natural frequencies of the bridg...

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Bibliographic Details
Published inAdvances in Civil Engineering Vol. 2020; no. 2020; pp. 1 - 13
Main Authors Ma, Laijing, Fang, Yilin, Li, Zheng, Li, Yinxin, Chen, Daihai, Ma, Fengrui
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 2020
Hindawi
John Wiley & Sons, Inc
Hindawi Limited
Wiley
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Summary:Taking a 62 m CFST bridge with a curved-string truss as the research object, according to its reinforcement scheme, the spatial finite element models of the bridge before and after reinforcement were established by using the general finite element software ANSYS. The natural frequencies of the bridge before and after reinforcement were calculated, and the seismic performance of the bridge was analyzed by using the response spectrum method. The results show that the frequencies of the reinforced bridges increase in varying degrees, especially the vertical and torsional frequencies. Before and after reinforcement, the maximum axial force in the upper chord of the bridge is the largest, and the shear force and bending moment are small. The maximum internal force appears at the two ends of the upper chord. This position should be regarded as the weak link of the bridge seismic resistance. Under the same conditions, the axial force of the bridge after reinforcement is reduced by about 30% compared with that before reinforcement, and the displacement of the bridge after reinforcement is reduced in varying degrees. The reinforcement measures can improve the lateral and vertical stiffness of the bridge, especially the stiffness of the deck system.
ISSN:1687-8086
1687-8094
DOI:10.1155/2020/4536365