Steel Railway Bridges Research Articles

Monitoring of a fatigue test on a full-size railway steel bridge with acoustic emission

Within the frame of the Rail4Future project (https://www.rail4future.com) co-funded by the Austrian Research Promotion Agency, a railway steel bridge was removed from the track and transported to a workshop in one piece. Artificial defects were introduced at different sections of the bridge structure as per advice of the scientific project partners in order to initiate fatigue cracks in the course of the subsequent fatigue test. One objective of the fatigue test was to identify suitable measurement and testing techniques for monitoring of fatigue crack growth. Among other techniques utilised by different project partners, acoustic emission monitoring was applied by TÜV AUSTRIA. This contribution describes the preparation as well as the performance of the acoustic emission monitoring and the results obtained. It is shown that this non-destructive testing technique is suitable for fatigue crack monitoring.

Supporting the infrastructure operators with customer specific AE-monitoring solutions

Cost-effective and efficient monitoring of infrastructure is crucial for planning maintenance and repairs while ensuring the safety of the structure. Acoustic emission is a method particularly suitable for long-term monitoring. However, the necessary extended monitoring period incurs high costs for the operator, primarily due to the exceptionally high costs of measuring equipment. The need for a tailored monitoring system for infrastructure applications is evident. TÜV AUSTRIA is developing a monitoring system called RISE, which represents a customized solution for steel bridge monitoring. The innovative online monitoring solution RISE assists experts with structural monitoring. Due to its compact design, low power consumption, and easy installation, the measuring system is specifically designed for continuous monitoring. Specifically, RISE is introduced for the hotspot monitoring of railway steel bridges. The passage of trains triggers a material response that can be recorded by the measuring system. This is used to perform crack monitoring on bridges and to have a tool for assessing crack activity and the degree of damage. This enables targeted planning of repairs and maintenance activities. Reducing the operating costs of the structure and ensures it save operation. The system is being developed to function robustly and provide a high level of automation. A demonstration of AE-monitoring of active cracks on a main bridge girder was done during a fatigue test in cooperation with the TU Graz. The girder was removed from a deconstructed bridge.

Prediction of fatigue life of a bolted joint in railway steel arch bridge using multiaxial fatigue criteria

Fatigue represents a critical condition for infrastructure subjected to repeated cyclic loads, such as steel railway bridges. The literature offers several methods to estimate fatigue life, consisting of three main phases: cycle counting, fatigue damage criterion, and damage accumulation criterion. Applying S-N curves might not be conservative in the case of railway bridges subjected to traffic because the stress-time history is complex and cannot be reduced to a sinusoidal history. Additionally, the presence of a multiaxial stress state must be considered. Therefore, this work compares eight multiaxial fatigue damage criteria for evaluating fatigue life in a scenario between high and low-cycle fatigue. Specifically, the authors considered four low-cycle fatigue criteria, namely Smith–Watson–Topper (SWT), Kandil, Brown and Miller (KBM), Glinka, Fatemi and Socie (FS), and four high-cycle fatigue criteria, Crossland, Basquin and the methods recommended by Eurocode 3 and British Standard. The rainflow counting method in ASTM E1049-85 (2011) and Miner’s rule for damage accumulation were used. The Polcevera railway steel bridge was selected as a case study. A 3D numerical model was developed for this purpose using Midas Civil software, taking into account the material non-linearity of the bridge’s elements. Once the area with the highest stress concentration was identified, a detailed analysis was conducted to estimate the stress and strain time histories induced by train traffic. A sensitivity analysis was conducted after critically comparing the eight methods for predicting fatigue life to assess the impact of traffic parameters, train velocity, axle load, and convoy length on fatigue life. It has been found that the criteria considering axial stress tend to overestimate the number of fatigue cycles to failure compared to the criteria, including the effect of shear stress components.

Development of a rating model for assessing the condition of steel railway bridges

Steel railway bridges play a crucial role in global transportation networks, yet their operational lifespan is often compromised by factors such as corrosion, aging, exposure conditions, and environmental challenges. Structural Health Monitoring (SHM) systems are widely employed to extend the longevity of these bridges. However, existing SHM models typically have limitations, as they tend to focus on a limited set of parameters, and their reliance on qualitative definitions introduces subjectivity into the evaluation process. To address these shortcomings, this research aims to develop an innovative priority weight-based condition rating model. Casual Factors (CF), laboratory and Non-Destructive Tests (NDT), Visual Inspection (VI), Environmental Conditions (EC), and Type of Element (TOE), were identified as main parameters to the condition assessment. Then, the research gathered opinions from 100 experts to establish the importance of these parameters. By averaging expert opinions and ensuring a high level of consistency (i.e. below 10%), the study aimed to minimize subjectivity. Numerical definitions were introduced to the model to enhance objectivity. The Fuzzy Analytical Hierarchy Process (FAHP) was employed to calculate appropriate weightings for the identified parameters, resulting in a comprehensive equation that encapsulates the main factors influencing the condition of steel railway bridges.To validate the developed rating model, a case study was conducted, analyzing seventeen railway bridges located in various regions of Sri Lanka. Notably, the model takes into account physical, geographical, and environmental conditions, making it applicable to diverse locations worldwide. This innovative approach contributes to the enhancement of steel railway bridge maintenance strategies, promoting their sustained and reliable operation on a global scale.

Lessons Learned From Inspecting Steel Railway Bridges In Egypt

Lessons Learned From Inspecting Steel Railway Bridges In Egypt

Destructive Testing of the Pinkabach Railway Bridge – Large scale Testing of Sensor Systems for Fatigue Crack Monitoring and System Identification

The work presents experiments carried out on an out-of-service steel railway bridge, the so called Pinkabach bridge. The objective was to test advanced and novel sensor systems, i.e. Distributed Fiber Optic Sensing (DFOS) and Acoustic Emission (AE), for the monitoring of fatigue cracks, both for crack initiation and subsequent crack growth, in steel railway bridges. Also, sensor systems for overall system identification, i.e. Tiny Motion (TM), Distributed Acoustic Sensing (DAS) and dynamic response analysis, have been tested. The Pinkabach bridge was a single span plate girder railway bridge with a span width of 21,5m that was taken out of service and transported to a secure environment that allowed for destructive testing with permanent access to the structure itself under controlled conditions. By harmonic excitation of the structure at its first resonance frequency, cyclic stress levels comparable to the stress levels during train passage were generated and it was possible to emulate the fatigue load from decades of train traffic within the limited period of the experiments. Crack initiation and growth happened at two locations of the flanges and crack growth was monitored till the crack length was half of the flange width of the main girder. To end the experiments a static load test showed the remaining capacity of the damaged structure. A conventional sensor system was used for validation and comparison with calculated predictions based on linear fracture mechanics, used for the design of the experiments. An overview over the whole set of experiments as well as (intermediate) results and findings on the applicability of the novel sensor systems are presented in this paper. The experiments are a collaborative work of multiple scientific and industrial partners and have been carried out as part of Area 3.1 of the COMET Project Rail4Future, funded by the Austrian Research Promotion Agency FFG.

Mode tracking for a steel railway bridge in presence of changing support conditions

Mode tracking for a steel railway bridge in presence of changing support conditions

Online Real-Time Monitoring System of A Structural Steel Railway Bridge Using Wireless Smart Sensors

In the transportation network, railway bridges are crucial for the transfer of both passengers and commodities. Railway bridges require continuous monitoring to observe their performance. A structural health monitoring system is one method for assessing the viability of a railway bridge structure. The functioning of railroad bridge structures has been extensively observed using wireless technology. This research aims to implement smart wireless sensors for monitoring the structural health of the railway bridge online in real-time during operation. Many sensor kinds were installed on the railway bridge, including strain gauges, accelerometers, linear variable displacement transducers, and proximity sensors. Geometric modeling and numerical simulation were performed to find critical frame locations on the railway bridge where the instrumentation sensors would be placed. In this study, MONITA® is employed for data acquisition modules. The MONITA® system consists of a combination of hardware and software that functions to retrieve, send, store, and process data. This paper describes the result of the establishment of this method to comprehend the performance of the steel railway bridge structure in real-time via the human-machine interface display dashboard. As a result, the monitoring system can appropriately be used to assess a structural railway bridge in real-time. This study may be helpful to practicing engineers and researchers in future studies of steel railway bridge evaluation. This could be a useful reference for future studies in implementing such systems as the railway bridge early warning system technique in detecting bridge damage.

Fatigue assessment of a 100-year-old riveted truss railway bridge

Fatigue is one of the most common reasons for failure in existing steel railway bridges, particularly with a riveted structure. Therefore, fatigue assessment is always the most important part of the complex evaluation of existing steel railway bridges. Additionally, a reliable fatigue assessment is often decisive in estimating the remaining service life of a bridge. The purpose of the presented research is to assess the fatigue of a 100-year-old riveted truss railway bridge. The assessment was carried out to decide whether the existing truss superstructure is still suitable for rehabilitation in the context of the ongoing modernisation of the railway line. The fatigue assessment procedure is based on the safe life method in the convention of nominal stresses. The Miner linear cumulative damage theory and the S-N curves according to the relevant European recommendations were also applied. Bridge evaluation revealed that the fatigue life of the steel superstructure was almost exhausted and that its remaining service life is too short to be considered for rehabilitation. It was also confirmed by the presence of fatigue cracks in the deck joints, detected during bridge inspection. Taking into account the assessment results, it was revealed that the existing riveted truss superstructure was not suitable for further use, which was intended to extend the bridge service life by the next 50 years after the modernisation of the railway line.

BEHAVIOR OF A STEEL STRUCTURE RAILWAY BRIDGE UNDER DYNAMIC LOADINGS

Most old steel structure railway bridges in Indonesia have deteriorated throughout their service life since they were constructed almost a century ago. However, those bridges' performance must be maintained to have essential safety issues and live extension of the railway bridge structure. Therefore, inspecting and evaluating those steel railway bridges is necessary to maintain the service requirement. Vertical deformation of the steel railway bridge caused by dynamic loadings needs to be observed. The objective of the study is to assess the old steel railway bridge by evaluating the strength characteristics of the structures against the working forces, particularly the moving, wind, and seismic loads. In order to understand the phenomena impacted by the dynamic loadings, the steel structure railway bridge was instrumented using deformation sensors, strain gages, accelerometers, and passive infrared. The steel railway bridge was analyzed using a 3D finite element model. This study discussed the influence of dynamic loadings on the steel structure railway bridge. This paper elaborates and provides suggestions to solve problems and recommended action in practice for future study. This paper may be useful for researchers and practicing engineers.

Vision‐based robust missing and loosened bolt detection for splice plate joints

SummaryVision‐based bolt defect detection methods based on feature changes have been reported. However, the robustness of key feature extraction and bolt detection requires improvement. This paper proposes a robust missing and loose bolt defect detection approach. The key features—reference points for perspective correction and the straight lines of the bolt edges—are extracted from the masks obtained by semantic segmentation models. The true and false bolt discrimination approach based on the mask shape can help improve bolt object detection accuracy. Overlapping between the bolt bounding boxes in the reference and detection images indicates missing bolts. The rotation angles reveal loosened bolts. The proposed approach was tested on fabricated bolted joint specimens and a steel railway bridge. The results suggest that these improvements ensure defect detection accuracy, with a miss rate of only 1% for missing bolt detection. Moreover, a loosened bolt with only 3° rotation is successfully detected. This approach has promising potential applicability in automatically detecting bolt defects in large steel structures.

Time-dependent fatigue reliability analysis of heavy-haul railway steel bridges

Fatigue of heavy-haul railway bridges has been an ongoing concern due to the excessive stresses and frequent cyclic effects of freight trains. Current fracture-based fatigue research, which promotes fatigue reliability analysis caused by crack propagation, is challenged by the dilemma between the detailed modeling of cyclic stress and the reflection of temporal characteristics of loading conditions. In addition, due to the strong non-Gaussian nature of the fatigue limit state function and the computational inefficiency of integrating finite element analysis, current time-dependent reliability methods need to be further developed. To evaluate the fatigue reliability of heavy-haul railway steel bridges considering the temporal dependence of cyclic train loading, a time-dependent fatigue reliability methodology is developed in this study with two innovations. Firstly, a cyclic stress range model is proposed based on the load analysis at the bridge level, which can capture the time-dependent characteristics of the incurred stress range throughout service life. Then, an improved outcrossing rate method for strong non-Gaussian fatigue limit state functions is developed to reduce the computational costs associated with reliability analysis integrated with the finite element model. The developed time-dependent fatigue reliability methodology is then applied to a heavy-haul railway steel truss bridge located in Shandong, China, which proves its efficiency and accuracy in evaluating the time-dependent fatigue reliability of heavy-haul railway steel bridges. Furthermore, the developed methodology is able to provide insight into the balance between bridge fatigue damage and freight volume, and it is found that the combination of small train axle weight and high operation frequency is the optimal solution to achieve the fatigue reliability of the steel bridge while fulfilling the freight demand.

Direct Analysis of a Steel Railway Bridge via Monitoring System of an Instrumented Structure

Railway infrastructure maintenance is essential in implementing the transportation system. Most of these railway bridges have suffered gradual deterioration over time. Predictive structural health monitoring (SHM) is required by installing instrumentation sensors on railway bridges to determine the condition of the railway bridge infrastructure at the site. This research aims to analyze and assess the existing condition of steel railway bridges to understand the load-deformation characteristics, bearing capacity, and dynamic response of the structure. This paper describes a valuable method for assessing the condition of steel railway bridges during operation. This paper presents a direct analysis of the steel railway bridge structure, with a span of 40.00 meters, a width of 4.40 meters, and a height of 6.60 meters. The steel structure railway bridge is modeled in 3D in detail, and numerical analysis is carried out using finite element analysis based on input parameters obtained from manual field measurements and instrumentation sensors. The expected result of the development of this SHM System is to know the performance of the steel railway bridge structure in real-time via the dashboard display. The results showed that the carrying capacity of the railway bridge was in a relatively safe condition. This case study may help practice engineers and researchers in future research. It can be a valuable reference for future research in developing and applying such a system to a typical case.

Identifying structural properties of a steel railway bridge for structural health monitoring using laser Doppler vibrometry

Steel railway bridges are indispensable to the safety, serviceability, and sustainability of the U.S. freight and rail network. Reduction in the stiffness of steel railway bridges is responsible for their strength-related and serviceability-related failure modes. Recent advances in the development of remote sensing techniques such as laser Doppler vibrometry (LDV) have enabled bridge engineers to assess the structural performance of bridges with the information that conventional visual inspection cannot provide. In this paper, experimental work and data analysis on the identification of structural parameters (generalized stiffness, generalized mass, and generalized damping) of a steel railway bridge under the application of a moving commuter train, using a portable LDV system, are presented. Background and train-induced vibration measurements (velocity and displacement) at the midspan of the bridge girder were measured. Time-domain displacement measurements in free vibration and forced vibration were used to identify the frequencies representing background noise (55.67 Hz), train loading (0.996 Hz), and the fundamental mode (8.698 Hz) of the bridge, using a single-degree-of-freedom bridge model. From the analysis, the damping ratio of the bridge was found to be 1.322% and the train speed to be 57.1706 mph (25.5575 m/s). A bounding approach was proposed to address the uncertainties in our calculations by providing the upper bound and the lower bound values of generalized stiffness, generalized mass, and generalized damping of the bridge. Monitoring the change in these structural properties can better assist decision makers in routine maintenance and asset management of steel railway bridges and other critical civil infrastructures.

Experimental Analysis of Static and Dynamic Performance for Continuous Warren Truss Steel Railway Bridge in Heavy Haul Railway

Continuous Warren truss steel railway bridges are one of the main forms of railway bridges. Due to the deterioration of materials and the long-term effect of loads, the bridges will inevitably experience performance degradation, which may lead to the failure of the bridge structure to continue to operate. In order to study the mechanical properties of steel structure bridges after material deterioration and long-term loads, a continuous Warren truss steel railway bridge that has been in operation for nearly 30 years (built in 1996) is used as the research object, and a combination of field tests and finite element (FE) simulations are used to carry out research on its mechanical properties under different loads. The research results show that after nearly 30 years of operation, the steel structure bridge has local damage, but the bearing capacity still meets the requirements of heavy-duty traffic. At this stage, the corrosion of the steel structure and the damage of the bearing should be repaired in time to prevent the damage from expanding.

Fatigue Life Assessment of a Steel Railway Bridge with Pot-PTFE Bearing

Fatigue Life Assessment of a Steel Railway Bridge with Pot-PTFE Bearing

Research on fatigue damage correction coefficient of main truss members of railway suspension bridges

Steel truss girder suspension bridges are gradually applied to long-span railway bridges. The fatigue damage correction factor is an important parameter for fatigue calculation, however the research on the coefficient is limited to small-span bridges. This paper analyzes force characteristics of main truss members, calculates the fatigue damage correction coefficient of truss members, and studies the influences of train loading length, annual traffic level of fatigue damage correction coefficient. The main conclusions are as follows: (1) The influence line and fatigue stress characteristics of the main truss members were studied; the stress range of members under tension or mainly under tension is analyzed, and the stress ranges and ratios between dead and live loads in main truss members are investigated. The results show that the maximum stress range of the bottom chord is 182 MPa, the ratios of dead to live loads of about 90 % of bottom chords and diagonal web members exceed the current specifications, and stress ratios of about 10 % of bottom chords and diagonal web members exceed the current specifications. (2) The fatigue damage correction coefficients of main truss members under different train loading lengths and annual traffic levels are calculated and recommended. The research results provide a basis for updating and supplementing the railway steel bridge code.

Temperature effect on the modal frequencies of a steel railway bridge

This paper presents the dynamic identification of the Ostiglia-Revere railway bridge, a steel truss girder bridge located in Northern Italy. The bridge is 6.6 m wide, about 940 m long and composed of 12 spans. The accelerations of a bridge span caused by both ambient excitation and train passages have been continuously measured from August to November. The monitoring system consists of 4 temperature sensors and 4 biaxial MEMS accelerometers, acquiring accelerations with a sampling frequency of 80 Hz. Modal properties are estimated adopting two different identification approaches, namely the Enhanced Frequency Domain Decomposition and the Stochastic Subspace Identification. Particular attention is paid to two crucial issues for vibration-based structural health monitoring: the recognition of the same structural mode from results identified during different time windows (i.e., mode clustering), and the temperature effect on estimated modal properties. As the latter is concerned, two regressive models, namely a linear regression model and an ARX model, are fitted to the frequency-temperature data, strongly reducing the eventuality of false vibration-based damage detections in the future.

Assessing the surface corrosion of a steel railway bridge using an active short-range remote sensing system

Assessing the surface corrosion of a steel railway bridge using an active short-range remote sensing system

Development of Rating System of Existing Railway Steel Bridges

Abstract: Railway bridges are designed to be serviceable for a long time. However, the structural conditions of railway bridges change over time due to environmental effects, fatigue and structurally unplanned modifications etc. which affect health of the structure significantly. Hence inspection and condition assessment of structure is required for their uninterrupted operation. Condition assessment is also required for maintenance and repairs of existing structures so as to avoid any mishaps and save valuable human life. Dealing with thousands of bridges and several factors that cause deterioration, makes the rating process extremely complicated. It is therefore necessary to develop a practical and accurate system, which will be capable of rating a network of railway bridges. Several bridge inspectionstandards and condition assessment practices have been developed around the globe. Some practices employ four linguistic expressions to rate bridge elements while other practices use five or six, or adopt numerical ratings such as 1 to 9. This research article introduces six colour codes in the proposed rating system for a network of railway bridges based on their current structural condition by means of visual inspection and different non-destructive evaluation techniques. The proposed rating system could provide bridge stakeholders with a rational appraising tool for condition assessment of railway bridges, allowing better allocation of budget and more precise maintenance decisions.