Existing Railway Steel Truss Bridge Static Experimental Analysis Based on Full-Bridge-Model

2013 ◽  
Vol 405-408 ◽  
pp. 1500-1503 ◽  
Author(s):  
Zhi Jie Sun ◽  
Yong Qian Liu
Keyword(s):  
Field Test ◽  
Element Model ◽  
Test Method ◽  
Evaluation Standard ◽  
Truss Bridges ◽  
Steel Truss Bridge ◽  
Bridge Model ◽  
Steel Truss ◽  
Static Performance ◽  
Truss Bridge

Combine the specific bridge, an analytical on the bridges static performance studied through the finite element model analysis and field test method. Summary and analyze the displacement and stress variation law of the main truss, longitudinal beams and beams which the bolt and weld superstructure steel truss bridges are effected by static loads, and compared field test results with theory value. Application practice proves that the evaluation standard and inspection of steel truss bridge is appropriate.

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.

Modeling and Dynamic Characteristics Analysis of the Qiantangjiang Rail-Cum-Road Bridge

2014 ◽  
Vol 501-504 ◽  
pp. 1187-1193 ◽  
Author(s):  
Hui Wang ◽  
He Xia ◽  
Jia Wang Zhan
Keyword(s):  
Dynamic Characteristics ◽  
Mode Shapes ◽  
Plate Element ◽  
Truss Bridges ◽  
Beam Elements ◽  
Steel Truss Bridge ◽  
Steel Truss ◽  
Characteristics Analysis ◽  
Truss Bridge ◽  
Steel Truss Bridges

The dynamic characteristics of the Qiantangjiang rail-cum-road steel truss bridge is to analyzed by the Beam elements Midas model, beam-Plate element Midas model and plate element Ansys model, and the calculated results are compared with the field experiment data. The natural frequencies and mode shapes simulated with the plate element Ansys model are much closer to the experimental ones, indicating it can more accurately simulate the dynamic characteristics of steel truss structure. The results can provide a reference for modeling the steel truss bridges, and as the foundation of further static and dynamic analyses.

A Study on the 3D Fine Model of a Large-Scale and Complicated Steel Truss Bridge

2011 ◽  
Vol 99-100 ◽  
pp. 383-387 ◽  
Author(s):  
Qun Wei ◽  
Hua Jiang ◽  
Sheng Ji Li
Keyword(s):  
Large Scale ◽  
Visual Analysis ◽  
Three Dimensional ◽  
Decision Makers ◽  
Data Conversion ◽  
Truss Bridges ◽  
Steel Truss Bridge ◽  
Steel Truss ◽  
Truss Bridge ◽  
Analysis Platform

The design and construction of the stiffening steel truss bridges is a complex and large-scale professional program. The abstract of the plans and the weaknesses of the view angles to the design sketch will also become limitations to the owners and the decision makers. Based on the project of River Baling Bridge of large stiffening steel truss girders, this study creates a three-dimensional fine model for it via CAD, pre-assembles each parts of the bridge, and checks sections and dockings one to one correspondingly. Data conversion of this model directly generates virtual visualized model. This visualized fine model of River Baling Bridge provides decision makers with a visual analysis platform, which also offers technical guarantee and support for sensible decision makings.

scholarly journals Structural Damage Localization and Quantification Based on a CEEMDAN Hilbert Transform Neural Network Approach: A Model Steel Truss Bridge Case Study

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1271 ◽  
Author(s):  
Asma Alsadat Mousavi ◽  
Chunwei Zhang ◽  
Sami F. Masri ◽  
Gholamreza Gholipour
Keyword(s):  
Neural Network ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Index ◽  
Steel Truss Bridge ◽  
Damage Indices ◽  
Bridge Model ◽  
Steel Truss ◽  
Truss Bridge

Vibrations of complex structures such as bridges mostly present nonlinear and non-stationary behaviors. Recently, one of the most common techniques to analyze the nonlinear and non-stationary structural response is Hilbert–Huang Transform (HHT). This paper aims to evaluate the performance of HHT based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique using an Artificial Neural Network (ANN) as a proposed damage detection methodology. The performance of the proposed method is investigated for damage detection of a scaled steel-truss bridge model which was experimentally established as the case study subjected to white noise excitations. To this end, four key features of the intrinsic mode function (IMF), including energy, instantaneous amplitude (IA), unwrapped phase, and instantaneous frequency (IF), are extracted to assess the presence, severity, and location of the damage. By analyzing the experimental results through different damage indices defined based on the extracted features, the capabilities of the CEEMDAN-HT-ANN model in detecting, addressing the location and classifying the severity of damage are efficiently concluded. In addition, the energy-based damage index demonstrates a more effective approach in detecting the damage compared to those based on IA and unwrapped phase parameters.

Structure Design of Car Overpass in the Urban Rail Construction

2014 ◽  
Vol 1006-1007 ◽  
pp. 38-41
Author(s):  
Lei Chen ◽  
Hong Sheng Qiu
Keyword(s):  
Three Dimensional ◽  
Element Model ◽  
Structure Design ◽  
Cable Stayed Bridge ◽  
Steel Truss Bridge ◽  
Steel Truss ◽  
Dimensional Finite Element ◽  
Girder Bridge ◽  
Three Dimensional Finite Element ◽  
Truss Bridge

The car overpass can play a significant role in easing traffic pressure. So for maximum easing traffic pressure, two types of car overpass are put forward: steel trussed girder-bridge and steel trussed cable-stayed bridge. Then establish a three-dimensional finite element model of the steel truss bridge and cable-stayed bridge by ANSYS. According to stress analysis and comparison of the steel truss and steel truss cable-stayed, the cable-stayed structure can enhance structural rigidity and strength, and have little influence on traffic.

Reliability Analysis of Continuous Steel Truss Bridge Stiffened with Rigid Cables Based on Stochastic Finite Element Method

2013 ◽  
Vol 639-640 ◽  
pp. 1060-1066
Author(s):  
Jian Liu ◽  
Yong Jian Liu
Keyword(s):  
Finite Element ◽  
Failure Probability ◽  
Reliability Index ◽  
Element Model ◽  
Stochastic Finite Element ◽  
Limit States ◽  
Steel Truss Bridge ◽  
Steel Truss ◽  
Strength And Stiffness ◽  
Truss Bridge

To analysis the reliability of Dongjiang Bridge, a steel truss bridge stiffened with rigid cables, a new analysis method that combined with each advantage of some common reliability computing method was put forward, which could get the probability distribution and numeric attributes of complex bridge structure's response expediently, and then get the reliability index and failure probability. A stochastic finite element model was established to analyze this bridge, in which some parameters such as material, geometric dimensioning, loads, and so on, were simulated as stochastic variables. The analysis result show that the lowest reliability index of main member bar's stress is 5.10, more than the allowable value 4.7, and the corresponding failure probability is 1.71×10-7. The reliability index of mid-span deflection in serviceability limit states reach up to 6.99 and its failure probability is 1.53×10-7. All results indicate that the strength and stiffness of Dongjiang Bridge has higher reliability.

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