Railway Truss Bridge Research Articles

Remote Inspection of Bridges with the Integration of Scanning Total Station and Unmanned Aerial Vehicle Data

Remote visual inspections are valuable tools for maintaining bridges in safe operation. In the case of old structures with incomplete documentation, the verification of dimensions is also an essential aspect. This paper presents an attempt to use a Scanning Total Station (STS) and Unmanned Aerial Vehicle (UAV) for the inspection and inventory of bridge dimensions. The STS’s measurements are conducted by applying two methods: the direct method using a total station (TS) and advanced geometric analyses of the collected point cloud. The UAV’s measurements use a Structure from Motion (SfM) method. Verification tests were conducted on a steel truss railway bridge over the largest river in Poland. The measurements concerned both the basic dimensions of the bridge and the details of a selected truss connection. The STS identified a significant deviation in the actual geometry of the measured connection and the design documentation. The UAV’s inspection confirmed these findings. The integration of STS and UAV technologies has demonstrated significant advantages, including STS’s high accuracy in direct measurements, with deviations within acceptable engineering tolerances (below a few mm), and the UAV’s efficiency in covering large areas, achieving over 90% compliance with reference dimensions. This combined approach not only reduces operating costs and enhances safety by minimizing the need for heavy machinery or scaffolding but also provides a more comprehensive understanding of the structural condition.

Evaluation of a permanent SHM system performance in detecting damage scenarios considering runnability thresholds

Due to an increasing number of bridges approaching the end of their design lives, there is a growing interest by the infrastructure managers on monitoring systems able to provide information on the service capability of structures. Focusing, in particular, on railway bridges, serviceability is related to both structural serviceability and runnability, where the first is related to the structural capability of the bridge, while the second is related to the constraints on rail geometry. In this work the authors present an investigation of the capability of a permanent monitoring system to detect the presence of damages that would lead to an exceedance of the structural threshold values imposed by runnability norms. The target structure is a double-span Warren truss railway bridge, located in Italy, designed in 1946 and currently instrumented with a permanent monitoring system. The latter performs dynamic, quasi-static and static measurements, with sensors ranging from velocimeters to end displacement transducers and clinometers. Thanks to a FE model of the actual structure, a set of damage scenarios can be simulated, defining the damage entities that lead to the exceedance of thresholds imposed by norms in terms of runability assessment. As a result, the installed sensors mesh was found to distinguish such critical structural conditions as well as lower entity damage scenarios. The paper discusses the capability of different sensor configurations and monitoring strategies (“dynamic”, “static”, etc) to detect such damage scenarios, in terms both of “early warning” capability and of minimum time required to detect the anomaly. The same approach can be extended to the analysis with respect to structural serviceability limits.

Model Updating and Assessment using Axial Strains for a Statically Determinate Truss Bridge

The safety of aging structures over the course of their service life is given by structural reliability. Additionally, there is a lack of techniques available for processing raw structural health monitoring (SHM) data in a way that makes it possible to validate and/or update structural reliability. Along with the diagnosis of structural anomaly using SHM techniques, the prognosis of structural condition is also an important aspect. Field-measured strain responses can be used as an indication of structural safety and provide information regarding the load-carrying capacity of the structure. Reliability assessment can be conducted only if a more accurate digital analogue is obtained for the actual bridge and when the structural responses can be predicted accurately. This paper validates a digital model of a real-life railway truss bridge. Pamban bridge is a century-old railway bridge having one track and four internally statically determinate truss leaves. Electrical strain gauges are instrumented to measure the axial strain responses in 84 out of 92 members of the bridge. Strain responses of 1072 train movements that traversed the bridge from 1st January 2021 to 14th July 2021 are recorded, and root mean square error (RMSE) between these field-measured strain responses and analytically computed strain responses from the digital model are estimated. The stationary trend of the time history of RMSE values depicts constant structural reliability. A technique is also proposed to forecast structural strain responses, which is validated with field-measured strain responses.

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.

Application of covariance statistical method for damage identification on railway truss bridge using acceleration response: experimental and numerical validation

This paper presents a novel statistical analysis-based approach to non-parametric damage detection in truss bridges. The method utilizes the normalized acceleration response time histories (NARTHs) of a bridge under random excitation. The coefficients of variation matrices are calculated using NARTHs for the truss bridge in both its baseline and damaged states. The results are shown as the difference in covariance matrices (DCMs) between the two conditions (pristine and damaged). The row or column-wise summation of the DCM matrix yields a summation of the difference in covariance matrix (SDCM) bar plot having one distinct peak for the damaged member. The location and relative severity of the damage can be determined by examining the DCM matrix and the SDCM bar plot. The variation in magnitude of the coefficients demonstrates the relative severity of damage. Experimental investigation of the proposed method for detecting damage on the truss bridge shows promising results. The approach is then numerically validated using a finite element model of a truss bridge. The proposed method effectively identified, located, and evaluated damage, even when the acceleration time histories are contaminated with noise. The case of multiple-member damage detection in the truss structure is further investigated in the study. The early detection of damage and monitoring of its progression through this method can assist in creating efficient maintenance strategies for truss bridge infrastructure.

Numerical Model Updating and Validation of a Truss Railway Bridge considering Train‐Track‐Bridge Interaction Dynamics

Numerical Model Updating and Validation of a Truss Railway Bridge considering Train‐Track‐Bridge Interaction Dynamics

UAV 3D Modeling and Application Based on Railroad Bridge Inspection

Unmanned aerial vehicle (UAV) remote sensing technology is vigorously driving the development of digital cities. For experimental objects such as large, protruding, and structurally complex steel truss railway bridge structures, commonly used oblique photography and cross-circular photography techniques can lead to blurring, missing, or lower accuracy of fine texture in the models. Therefore, this paper proposes a real-scene three-dimensional modeling method that combines oblique photography with inclined photography and compares it with oblique photography and cross-circular photography techniques. Experimental results demonstrate that the model generated by combining oblique photography with inclined photography exhibits clearer textures, more complete lines, and higher accuracy, meeting the accuracy requirements of 1:500 topographic map control points. This method plays a beneficial auxiliary role in the inspection of ailments such as steel structure coating corrosion and high-strength bolt loss in steel truss railway arch bridges.

Damage Identification of Railway Bridges through Temporal Autoregressive Modeling.

The damage identification of railway bridges poses a formidable challenge given the large variability in the environmental and operational conditions that such structures are subjected to along their lifespan. To address this challenge, this paper proposes a novel damage identification approach exploiting continuously extracted time series of autoregressive (AR) coefficients from strain data with moving train loads as highly sensitive damage features. Through a statistical pattern recognition algorithm involving data clustering and quality control charts, the proposed approach offers a set of sensor-level damage indicators with damage detection, quantification, and localization capabilities. The effectiveness of the developed approach is appraised through two case studies, involving a theoretical simply supported beam and a real-world in-operation railway bridge. The latter corresponds to the Mascarat Viaduct, a 20th century historical steel truss railway bridge that remains active in TRAM line 9 in the province of Alicante, Spain. A detailed 3D finite element model (FEM) of the viaduct was defined and experimentally validated. On this basis, an extensive synthetic dataset was constructed accounting for both environmental and operational conditions, as well as a variety of damage scenarios of increasing severity. Overall, the presented results and discussion evidence the superior performance of strain measurements over acceleration, offering great potential for unsupervised damage detection with full damage identification capabilities (detection, quantification, and localization).

Case Study of Old Steel Riveted Railway Truss Bridge: From Material Characterization to Structural Analysis

The structural analysis of an old steel riveted railway truss bridge located over the Maruska River on the Działdowo – Olsztyn, Poland railway line is performed in this paper to check its behaviour under today’s railway loads. The mechanical properties of construction steel extracted from the old steel bridge are investigated by tensile tests, impact tests through the Charpy pendulum impact V-notch, and an optical emission spectrometer. Structural analysis exhibits that the steel bridge requires proper structural bridge improvements to meet today’s load requirements in terms of bearing capacity and serviceability state. The paper begins with a wide survey of literature carried out on the investigation of steel riveted railway bridge subject matter. This paper can provide scientists, engineers, and designers with an experimental and structural basis in the field of old steel riveted railway truss bridge construction.

Measurement of Geometric Variations of a Railway Truss Bridge (Case Study: BH77 Railway Bridge)

Monitoring the condition of the railway track on a regular basis needs to be carried out regularly to minimize risk. One of the causes of the decrease in the strength of the bridge structure can be caused by changes in cross-sectional dimensions. The existing dimensions of the bridge structure need to be known because they will affect the steel frame profile area, where the steel frame area will affect the size or the small value of the deflection and stress of the bridge structure. The dimensions of the frame need to be seriously considered so that the stress and deflection values ??of the bridge structure remain constant. This research was conducted at the BH 77 Railway Bridge in Tegineneng, Tanjungkarang-Martapura, Lampung, which uses a type frame configuration warren truss. This location was chosen to fit the research that was also conducted by Badan Riset dan Inovasi Nasional (National Research and Innovation Agency of Indonesia). Based on the measurement of the dimensions of the bridge truss that has been carried out, the results show that there is a difference in the value of the circumference of each rod with the standard deviation for each similar profile. The biggest difference in the circumference of the truss is the profile of H beam, 113 and 115 rods with dimensions of 340×300×15×18, the initial circumference value is 1,280 mm, and after the measurement is 1,289.42 mm with a standard deviation value of 0.91 mm. while for the smallest difference, namely the H beam profile, rod 110 with dimensions of 340×310×39×21, the initial circumference value is 1,300 mm and after the measurement is 1,300.33 mm with a standard deviation value of 0.24 mm.

Structural Health Monitoring of a steel truss railway bridge studying its low frequency response

AbstractIn the framework of direct Structural Health Monitoring approaches, this paper presents a low frequency range analysis performed on a steel truss bridge designed in 1946 and built up in Northern Italy. The bridge is instrumented with a permanent structural health monitoring system, that guarantees a continuous flux of data and information from a heterogeneous set of sensors. In this analysis, static and quasistatic bridge responses are considered. These experimental data are merged with the analogous outputs obtained from numerical simulations, performed on FE models representative of the actual bridge, with the purpose of identifying damage‐sensitive indexes. Simulations are performed considering the healthy structure and modelling different damage scenarios. The static analysis consists in the construction of a regressive model able to estimate sensor output responses starting from environmental measurements, with the primary purpose to reduce the effect of temperature over measured static response. This procedure allows to relate the damages simulated by means of a numerical model with the real data, so that the monitoring rules can effectively defined.

Study on damage identification of High-Speed railway truss bridge based on statistical steady-state strain characteristic function

The localization and quantification of damage in bridge structures have always been a challenging problem, especially for high-speed railway truss bridges with intricate structural forms and complex load conditions. To address this issue, this paper proposes a novel damage indicator based on strain characteristic functions, and integrated it into an automated framework for real-time damage detection which is particularly suitable for in-service structural health monitoring applications. To evaluate the effectiveness of this approach, a study is conducted using a finite element digital twin model to simulate the structural responses at critical areas of high-speed railway truss bridges under train-induced loads. The proposed damage indicator of the model was used to investigate and evaluate different types of bridge damage, reflecting both the location and severity of damage in high-speed railway truss bridges. The results suggest that the proposed damage indicator, when used with a distributed sensor system, shows promise in accurately locating and measuring damage in high-speed railway truss bridges. In addition, for the bridge health monitoring system with sparse sensor distribution, this indicator can provide a probability assessment of various damage conditions of a high-speed railway truss bridge. This information could potentially assist in the process of conducting in-service maintenance of a high-speed railway truss bridge.

Experimental analysis of the railway truss bridge using modern methods

Experimental analyses of civil engineering structures have been carried out for decades. While in the past, mainly static load tests of new structures were performed, a few severe accidents with fatal results caused a lot of emphasis to be given to monitoring existing structures recently. The need for continuous or periodical evaluation of static or dynamic behaviour of structures in operation led to a good progress in the development of modern methods for experimental analysis. The paper deals with one of the modern methods of experimental analysis – the DIC method. Possible application of the DIC method was verified by an experimental analysis of a railway truss bridge in Rataje nad Sázavou. The experiment was divided into two stages. During the experiment, deflections of the bridge measured by LVDT sensors and the DIC method were compared. Technological problems of the DIC method were found in the first stage. One of the problems was related to stability of the camera tripod. A solution was proposed and verified during the second stage.

Performance assessment of steel truss railway bridge with curved track

Non-destructive Structural Health Monitoring techniques can be incorporated into bridge integrity management by assessing structural conditions. This paper describes a performance assessment of a steel truss railway bridge in Bratislava using vibration-based techniques as a further part of maintenance in addition to standard visual inspections. To obtain the necessary data, a multipurpose measuring system was used. Various types of data were measured, e.g. accelerations, strains, and displacements. The advantage of the multipurpose measuring system was that the traffic over the bridge was not restricted, even though the bridge carries only a single curved track. Two test campaigns were conducted to assess the performance of the bridge. One campaign was devoted to measuring ambient vibrations in order to perform the operational modal analysis, and the second was carried out to measure strains and displacements during a train passage. The results show a successful system identification of the structure using ambient vibrations; and a finite element model was verified and validated by a comparison of strains and displacements, as well as by modal parameters. According to the results obtained, the structural health of the investigated bridge was satisfactory.

Modification of an Existing Steel Truss Railway Bridge for Installation of Railway Overhead Electrification System

Modification of an Existing Steel Truss Railway Bridge for Installation of Railway Overhead Electrification System

Robust correlation mapping of train-induced stresses for high-speed railway bridge using convolutional denoising autoencoder

Train-induced stresses in different monitoring points not only reflects local mechanical characteristics of the structural components but also has inherent spatiotemporal correlations in the high-speed railway bridges. Mapping correlations among the stress responses can assist recognizing train-induced stress pattern and lay foundation for structural health diagnosis. However, correlation mapping and feature extraction of structural responses rely heavily on the data integrity, the pre-constructed model may be out of action due to data acquisition/transmission error, sensor faults, etc., commonly exists in the structural health monitoring system. Considering the characteristics of various incomplete train-induced stresses, this study presents a robust correlation mapping of incomplete data to complete data using one-dimensional convolutional denoising autoencoder. Stacked convolutional layers are employed as encoder to extract robust spatiotemporal feature of incomplete stresses, and transposed convolutional layers served as decoder to reconstruct denoised and complete stresses. In the training strategy, various incomplete data conditions, where stress data are lost continuously or discretely with different missing rates, are considered as training samples, making the established correlation mapping robust, accurate, and adaptive. The application on a high-speed railway truss bridge demonstrates that the proposed method can robustly reconstruct the complete stress data under different data loss conditions. The method can also be employed to assess the importance of any sensor combinations to the monitoring item, which shed light on the maintenance of sensor network.

Development of a Novel Damage Detection Framework for Truss Railway Bridges Using Operational Acceleration and Strain Response

Railway bridges are an integral part of any railway communication network. As more and more railway bridges are showing signs of deterioration due to various natural and artificial causes, it is becoming increasingly imperative to develop effective health monitoring strategies specifically tailored to railway bridges. This paper presents a new damage detection framework for element level damage identification, for railway truss bridges, that combines the analysis of acceleration and strain responses. For this research, operational acceleration and strain time-history responses are obtained in response to the passage of trains. The acceleration response is analyzed through a sensor-clustering-based time-series analysis method and damage features are investigated in terms of structural nodes from the truss bridge. The strain data is analyzed through principal component analysis and provides information on damage from instrumented truss elements. A new damage index is developed by formulating a strategy to combine the damage features obtained individually from both acceleration and strain analysis. The proposed method is validated through a numerical study by utilizing a finite element model of a railway truss bridge. It is shown that while both methods individually can provide information on damage location, and severity, the new framework helps to provide substantially improved damage localization and can overcome the limitations of individual analysis.

Thermal challenges of replacing jointed rails with CWR on steel railway bridges

Visual inspection of a steel truss railway bridge revealed multiple fatigue cracks on the top member of the truss, mainly attributed to the high impact loads of crossing wheels over the jointed tracks on the bridge. The proposal to replace the jointed track with continuously welded rails (CWR) raised a number of issues regarding the thermal interaction of track and bridge, as the bridge experiences extreme temperature variations. Incorporation of high longitudinal restraint between the track and the bridge may increase the risk of track buckling failure at bridge transition zones, since bridge thermal expansion during hot weather can add compressive forces to the rails transferred through the track fastening system. Reducing longitudinal restraining may increase the size of a rail gap resulting from cold weather rail fracture. An optimal longitudinal fastening profile between the bridge and the track therefore is required to mitigate thermal issues both in hot summers and cold winters. To do so, a numerical model of the track and the bridge is developed in Abaqus and calibrated based on the results of tests performed on the bridge and available literature. Three longitudinal fastening profiles between the bridge and the track are introduced in the numerical model and performance of each for mitigating buckling failure and cold weather rail fracture are analyzed. It is concluded that providing 50% resilient fasteners and 50% zero toe load fasteners on each span can be a sound approach to mitigating the thermal issues of CWR tracks on the bridge.

Fatigue assessment of 100 years old riveted truss railway bridge

Fatigue is one of the most often reasons for failure in existing steel bridges, particularly with riveted structure. Therefore fatigue assessment is always the most important part of the complex evaluation of existing steel bridges. The reliable fatigue assessment is often decisive in the estimation of the remaining service life of a bridge. The example of a comprehensive fatigue assessment of 100 years old riveted truss railway bridge, based on European procedures and codes, has been presented in the paper. The applied procedure is based on the safe life method in the convention of nominal stresses. The bridge assessment revealed, that the remaining fatigue strength was almost exhausted and the further service life of the bridge was close to zero. Taking into account the assessment results it was also revealed, that the existing riveted truss superstructure was not suitable for further use in the railway bridge after its rehabilitation, which aimed to extend the bridge service life by the next 50 years. Keywords: Railway bridge; Steel structure; Truss, riveted joints; Fatigue life

Evaluation of DAF For Steel Truss Railway Bridge Using Experimental and Numerical Approach. (Dept. C)

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