Abstract

Span lengths of newly constructed cable-stayed railway bridges continue to show increases relative to those of older bridges. Accompanying such increases is the importance of ensuring that vibrations of long-span cable-stayed bridges satisfy both safety and serviceability requirements, particularly for bridges that support train passages. In contrast to modern design of bridges that support roadway vehicles, current methods for analyzing cable-stayed railway bridges do not yet typically account for coupling effects that may occur between cables and the surrounding bridge structure during train passages. This paper presents a computational framework for the nonlinear dynamic analysis of railway bridges based on a coupled train–bridge analytical model and investigates the significance of accounting for cable-related coupling effects. A case study is then carried out, where coupled dynamic responses of cables, towers, and girders of an in-service railway bridge are computed and compared to those obtained using an uncoupled approach. These comparisons demonstrate the merits of accounting for coupling phenomena when computing dynamic characteristics of cable-stayed railway bridges and highlight benefits of the coupled analysis approach in bridge design applications.

Document Type

Article

Publication Date

6-2019

Notes/Citation Information

Published in International Journal of Advanced Structural Engineering, v. 11, issue 2, p. 271-283.

© The Author(s) 2019

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Digital Object Identifier (DOI)

https://doi.org/10.1007/s40091-019-0229-1

Funding Information

The authors are grateful to the financial support provided by the National Natural Science Foundation of China (Nos. 51378021 and 11572117) and Hunan Province University Innovation Platform Open Foundation Project (13K006).

Share

COinS