Dynamic Performance Analysis of Steel Truss Bridge

2013 ◽  
Vol 423-426 ◽  
pp. 1548-1551
Author(s):  
Shan Shan Wang ◽  
Tao Xu ◽  
Si Feng Qin ◽  
Yun Jie Zhang
Keyword(s):  
Seismic Waves ◽  
Response Spectrum ◽  
Dynamic Performance ◽  
Time History ◽  
Displacement Curve ◽  
Maximum Deformation ◽  
Steel Truss Bridge ◽  
Steel Truss ◽  
Truss Bridge ◽  
Dynamic Performance Analysis

Steel truss bridge is an important part of transportation hub and lifeline engineering, it recently has attracted more attention on dynamic performance of steel truss bridge. In this paper, the ANSYS software is used to perform the modal analysis of steel truss bridge, and we find that the main bridge are more sensitive to the vertical earthquake (i.e., Y direction). In the earthquake response spectrum analysis on Y direction, we find that the maximum deformation is at mid-span of steel truss bridge. In the transient analysis of seismic waves, under the action of horizontal and vertical earthquake accelerations, the structure displacement dynamic diagram and time-history displacement curve are obtained and some conclusions are drawn.

Vibration Analysis of Bridge Structure under Moving Train Load and Earthquake Action

2014 ◽  
Vol 501-504 ◽  
pp. 1266-1269 ◽  
Author(s):  
Bei Bei Fan ◽  
Yuan Zhang ◽  
Dong Hua Ruan
Keyword(s):  
Dynamic Response ◽  
Time History ◽  
Dynamic Effect ◽  
Bridge Structure ◽  
Steel Truss Bridge ◽  
History Analysis ◽  
Steel Truss ◽  
Earthquake Action ◽  
Truss Bridge ◽  
Moving Train

In this paper, vibration of a steel truss bridge under moving train and earthquake action is analyzed. The following conclusions are drawn by modal analysis and time-history analysis. 1) Lateral dynamic response of this structure is more obvious under earthquake action and lateral dynamic effect of train running load; 2) seismic response in the directions different from train load is small, and dynamic response becomes larger obviously when they are considered together.

Deconstruction Monitoring of a Steel Truss Bridge

2017 ◽  
Vol 2642 (1) ◽  
pp. 139-146
Author(s):  
Matthew Yarnold ◽  
Stephen Salaman ◽  
Eric James
Keyword(s):  
Steel Truss Bridge ◽  
Steel Truss ◽  
Truss Bridge

scholarly journals A Bayesian Belief Network method for bridge deterioration detection

2020 ◽  
pp. 1748006X2097922
Author(s):  
Matteo Vagnoli ◽  
Rasa Remenyte-Prescott ◽  
John Andrews
Keyword(s):  
Element Model ◽  
Bayesian Belief Network ◽  
Geographic Area ◽  
Detection Methods ◽  
Health State ◽  
Belief Network ◽  
Steel Truss Bridge ◽  
Steel Truss ◽  
Network Method ◽  
Truss Bridge

Bridges are one of the most important assets of transportation networks. A closure of a bridge can increase the vulnerability of the geographic area served by such networks, as it reduces the number of available routes. Condition monitoring and deterioration detection methods can be used to monitor the health state of a bridge and enable detection of early signs of deterioration. In this paper, a novel Bayesian Belief Network (BBN) methodology for bridge deterioration detection is proposed. A method to build a BBN structure and to define the Conditional Probability Tables (CPTs) is presented first. Then evidence of the bridge behaviour (such as bridge displacement or acceleration due to traffic) is used as an input to the BBN model, the probability of the health state of whole bridge and its elements is updated and the levels of deterioration are detected. The methodology is illustrated using a Finite Element Model (FEM) of a steel truss bridge, and for an in-field post-tensioned concrete bridge.

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