Reliability assessment of railway bridges subjected to high-speed trains considering the effects of seasonal temperature changes

2016 ◽  
Vol 126 ◽  
pp. 712-724 ◽  
Author(s):  
P. Salcher ◽  
H. Pradlwarter ◽  
C. Adam
Keyword(s):  
High Speed ◽  
Reliability Assessment ◽  
Seasonal Temperature ◽  
Railway Bridges ◽  
Temperature Changes ◽  
High Speed Trains

scholarly journals On the optimal strategy of stochastic-based reliability assessment of railway bridges for high-speed trains

Meccanica ◽  
2019 ◽  
Vol 54 (9) ◽  
pp. 1385-1402 ◽  
Author(s):  
Benjamin Hirzinger ◽  
Christoph Adam ◽  
Patrick Salcher ◽  
Michael Oberguggenberger
Keyword(s):  
Optimal Strategy ◽  
High Speed ◽  
Reliability Assessment ◽  
Railway Bridges ◽  
High Speed Trains

Nonlinear Vibration and Comfort Analysis of High-Speed Trains Moving Over Railway Bridges

Volume 2 ◽  
2004 ◽  
Author(s):  
M. H. Kargarnovin ◽  
D. Younesian ◽  
D. J. Thompson ◽  
C. J. C. Jones
Keyword(s):  
High Speed ◽  
Ride Comfort ◽  
Beam Theory ◽  
Maximum Acceleration ◽  
Railway Bridges ◽  
Comfort Index ◽  
Power Spectral ◽  
High Speed Trains ◽  
Train Speed ◽  
Track Bridge

The ride comfort of high-speed trains passing over railway bridges is studied in this paper. The effects of some nonlinear parameters in a carriage-track-bridge system are investigated such as the load-stiffening characteristics of the rail-pad and the ballast, rubber elements in the primary and secondary suspensions systems. The influence of the track irregularity and train speed on two comfort indicators, namely Sperling’s comfort index and the maximum acceleration level, are also studied. Timoshenko beam theory is used for modelling the rail and bridge and two layers of parallel damped springs in conjunction with a layer of mass are used to model the rail-pads, sleepers and ballast. A randomly irregular vertical track profile is modelled, characterised by a power spectral density (PSD). The ‘roughness’ is generated for three classes of tracks. Nonlinear Hertz theory is used for modelling the wheel-rail contact.

scholarly journals Effect of High-Speed Train-Induced Wind on Trackside UAV Thrust Near Railway Bridge

2020 ◽  
Vol 10 (10) ◽  
pp. 3495 ◽  
Author(s):  
Hyuk-Jin Yoon ◽  
Su-Hwan Yun ◽  
Dae-Hyun Kim ◽  
Jae Hee Kim ◽  
Bong-Kwan Cho ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Wind Velocity ◽  
High Speed ◽  
Railway Bridge ◽  
High Speed Train ◽  
Box Girder ◽  
Railway Bridges ◽  
High Speed Trains ◽  
Thrust Measurement ◽  
Girder Bridge

Imaging devices attached to unmanned aerial vehicles (UAVs) are used for crack measurements of railway bridges constructed for high-speed trains. This research aims to investigate track-side wind induced by high-speed trains and its effect on UAV thrust near the railway bridge. Furthermore, the characteristics of train-induced wind in three axial directions along a track, wind velocity, and the effect of train-induced wind on the UAV thrust were analyzed. This was achieved by installing 3-axis ultrasonic anemometers and a UAV thrust measurement system on top of a PSC box girder bridge. The changes in the train-induced wind velocity were monitored along the train travel, width, and height directions. The train-induced wind was measured at distances of 0.8, 1.3, 2.3, and 2.8 m away from the train’s body to analyze wind velocity based on distance. It was found that the maximum wind velocity decreased linearly as the distance from the train’s body increased. The UAV thrust increased by up to 20% and 60%, owing to train-induced wind when the leading and trailing power cars of a high-speed train passed, respectively. Thus, it is necessary to conduct further research to develop robust control and a variable pitch-propeller that can control thrust.

Mapping relationship between dynamic responses of high-speed trains and additional bridge deformations

2020 ◽  
pp. 107754632093689
Author(s):  
Hongye Gou ◽  
Chang Liu ◽  
Hui Hua ◽  
Yi Bao ◽  
Qianhui Pu
Keyword(s):  
High Speed ◽  
Coupled Model ◽  
Dynamic Responses ◽  
High Speed Railway ◽  
Railway Bridges ◽  
Running Safety ◽  
High Speed Trains ◽  
Track Bridge ◽  
The Relationship ◽  
Track Deformation

Deformations of high-speed railways accumulate over time and affect the geometry of the track, thus affecting the running safety of trains. This article proposes a new method to map the relationship between dynamic responses of high-speed trains and additional bridge deformations. A train–track–bridge coupled model is established to determine relationship between the dynamic responses (e.g. accelerations and wheel–rail forces) of the high-speed trains and the track deformations caused by bridge pier settlement, girder end rotation, and girder camber. The dynamic responses are correlated with the track deformation. The mapping relationship between bridge deformations and running safety of trains is determined. To satisfy the requirements of safety and riding comfort, the suggested upper thresholds of pier settlement, girder end rotation, and girder camber are 22.6 mm, 0.92‰ rad, and 17.2 mm, respectively. This study provides a method that is convenient for engineers in evaluation and maintenance of high-speed railway bridges.

scholarly journals Sensor data-based probabilistic monitoring of time-history deflections of railway bridges induced by high-speed trains

2022 ◽  
pp. 147592172110634
Author(s):  
Jaebeom Lee ◽  
Seunghoo Jeong ◽  
Junhwa Lee ◽  
Sung-Han Sim ◽  
Kyoung-Chan Lee ◽  
...  
Keyword(s):  
High Speed ◽  
Time History ◽  
Training Data ◽  
Sensor Data ◽  
Data Synchronization ◽  
Speed Estimation ◽  
Railway Bridges ◽  
Monitoring Model ◽  
High Speed Trains ◽  
Probabilistic Monitoring

Structural condition monitoring of railway bridges has been emphasized for guaranteeing the passenger comfort and safety. Various attempts have been made to monitor structural conditions, but many of them have focused on monitoring dynamic characteristics in frequency domain representation which requires additional data transformation. Occurrence of abnormal structural responses, however, can be intuitively detected by directly monitoring the time-history responses, and it may give information including the time to occur the abnormal responses and the magnitude of the dynamic amplification. Therefore, this study suggests a new Bayesian method for directly monitoring the time-history deflections induced by high-speed trains. To train the monitoring model, the data preprocessing of speed estimation and data synchronization are conducted first for the given training data of the raw time-history deflection; the Bayesian inference is then introduced for the derivation of the probability-based dynamic thresholds for each train type. After constructing the model, the detection of the abnormal deflection data is proceeded. The speed estimation and data synchronization are conducted again for the test data, and the anomaly score and ratio are estimated based on the probabilistic monitoring model. A warning is generated if the anomaly ratio is at an unacceptable level; otherwise, the deflection is considered as a normal condition. A high-speed railway bridge in operation is chosen for the verification of the proposed method, in which a probabilistic monitoring model is constructed from displacement time-histories during train passage. It is shown that the model can specify an anomaly of a train-track-bridge system.

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