Search Results (36)

The 2026 opening of the Gordie Howe International Bridge between Windsor, Ontario, Canada and Detroit, Michigan, USA, with its multi-use trail for cyclists and pedestrians, is projected to catalyze cross-border trail tourism and help further revitalize these two border cities. Both Windsor and Detroit have unique, extensive trail systems with compelling destinations. However, cross-border trail tourism institutionalization needs improvement. Tourism, greenway, and destination partners should explore creating a boundary organization to foster and market cross-border trail tourism. Recommendations from a 2024 cross-border trail tourism conference include: develop strategies for community engagement and storytelling to enhance cultural connections between regions; strengthen ties between trail groups and environmental organizations to provide trail experiences that reconnect people with the river and other natural resources; support the region’s efforts to obtain a UNESCO World Heritage Site designation for the Underground Railroad and support the Canadian federal designation of Windsor’s Ojibway National Urban Park; strengthen collaborations between tourism and cycling partners to promote and market cross-border trail tourism; institutionalize greenway assessments (every 5–10 years) to evaluate trail segment completions, gaps, potential route improvements, safety improvements, equity considerations, etc., and to keep greenways in the public consciousness; and measure and broadly communicate the economic impact of cross-border trail tourism resulting from the bridge. Full article

Floods pose a substantial risk to human well-being. These risks encompass economic losses, infrastructural damage, disruption of daily life, and potential loss of life. This study presents a state-wide and county-level spatial exposure assessment of the Iowa railway network, emphasizing the resilience and reliability of essential services during such disasters. In the United States, the railway network is vital for the distribution of goods and services. This research specifically targets the railway network in Iowa, a state where the impact of flooding on railways has not been extensively studied. We employ comprehensive GIS analysis to assess the vulnerability of the railway network, bridges, rail crossings, and facilities under 100- and 500-year flood scenarios at the state level. Additionally, we conducted a detailed investigation into the most flood-affected counties, focusing on the susceptibility of railway bridges. Our state-wide analysis reveals that, in a 100-year flood scenario, up to 9% of railroads, 8% of rail crossings, 58% of bridges, and 6% of facilities are impacted. In a 500-year flood scenario, these figures increase to 16%, 14%, 61%, and 13%, respectively. Furthermore, our secondary analysis using flood depth maps indicates that approximately half of the railway bridges in the flood zones of the studied counties could become non-functional in both flood scenarios. These findings are crucial for developing effective disaster risk management plans and strategies, ensuring adequate preparedness for the impacts of flooding on railway infrastructure. Full article

Aging railroad bridges present complex challenges due to advancing deterioration and outdated design assumptions. This study develops a comprehensive analytical approach for assessing an aging steel truss railroad bridge through finite element (FE) modeling, sensitivity analysis, and model updating, supported by field testing. An initial FE model of the bridge was created based on original drawings and field observations. Field testing using a laser Doppler vibrometer captured the bridge’s dynamic response (vibrations and deflections) under regular train traffic. Key structural parameters (material properties, section properties, support conditions) were identified and varied in a sensitivity analysis to determine their influence on model outputs. A hybrid sensitivity analysis combining log-normal sampling and a genetic algorithm (GA) was employed to explore the parameter space and calibrate the model. The GA optimization tuned the FE model parameters to minimize discrepancies between simulated results and field measurements, focusing on vertical deflections and natural frequencies. The updated FE model showed significantly improved agreement with observed behavior; for example, vertical deflections under a representative train were matched within a few percent, and natural frequencies were accurately reproduced. This validated model provides a more reliable tool for predicting structural performance and fatigue life under various loading scenarios. The results demonstrate that integrating field data, sensitivity analysis, and model updating can greatly enhance the accuracy of structural assessments for aging railroad bridges, supporting more informed maintenance and management decisions. Full article

This study addresses the water basin effect in the underwater sand layer of steel pipe pile cofferdams by integrating the concept from building foundation pits to cofferdam foundation pit analysis. A theoretical derivation is presented for the deformation evolution of steel pipe piles and bottom seals within the cofferdam pit. The cofferdam construction dewatering process is divided into four stages: riverbed excavation for bottom sealing, dewatering to the second support, dewatering to the third support, and dewatering to final bottom sealing. The steel pipe piles are modeled as single-span or multi-span cantilever continuous beam structures. Using the superposition principle, deformation evolution equations for these statically indeterminate structures across the four stages are derived. The bottom seal is simplified to a single-span end-fixed beam, and its deflection curve equation under uniform load and end-fixed additional load is obtained via the same principle. A case study based on the 6# pier steel pipe pile cofferdam of Xi’an Metro Line 10 Jingwei Bridge rail-road project employs FLAC3D for hydrological–mechanical coupling analysis of the entire dewatering process to validate the water basin effect. Results reveal a unique water basin effect in cofferdam foundation pits. Consistent horizontal deformation patterns of steel pipe piles occur across all working conditions, with maximum horizontal displacement (20.72 mm) observed at 14 m below the pile top during main pier construction completion. Close agreements are found among theoretical, numerical, and monitored deformation results for both steel pipe piles and bottom seals. Proper utilization of the formed water basin effect can effectively enhance cofferdam stability. These findings offer insights for similar engineering applications. Full article

This study investigated the impact coefficient of a large-span steel truss arch railroad bridge under moving train loads, with the Nanning Three Banks Yongjiang Special Bridge serving as the case study. Field tests were conducted to measure the bridge’s self-vibration characteristics, dynamic deflection, and strain. A coupled vehicle–bridge vibration model was developed using the finite element software ABAQUS 2022 for the bridge and multi-body dynamics software SIMPACK 2022 for the CRH2 train. The two models were integrated to simulate the dynamic interaction between the train and bridge under different speeds and single-/double-track operations. The results demonstrate that the joint simulation of SIMPACK and ABAQUS was an effective method for the vehicle–bridge coupled vibration analysis. The key findings include the following: the deflection and stress impact coefficients increased with the train speed, where the main span exhibited larger deflection coefficients than the side span. The stress impact coefficients varied significantly across different bridge components, where the lower chord of the side span and the ties of the main span showed the highest values. While there was no substantial difference in the deflection impact coefficients between the single- and double-track operations, the stress impact coefficients showed deviations, particularly in the side span’s lower chord and ties, highlighting their sensitivity to vehicle-induced deflection. This study concluded that the bridge’s deflection impact coefficient met design specifications, but the stress impact coefficient exceeded the specified values, suggesting that stress amplification should be carefully considered in the design of similar bridges to ensure operational safety. Full article

A model transformation method based on state refinement and semantic mapping is proposed to address the challenges of high modeling complexity and resource consumption in symbolic validation of industrial software requirements. First, a rule-based semantic mapping system is constructed through the explicit definition of element correspondence between statechart components and verification models, coupled with a composite state-level refinement strategy to structurally optimize model hierarchy. Second, an automated transformation algorithm is developed to bridge graphical modeling tools with formal verification environments, supported by quantitative evaluation metrics for mapping validity. To demonstrate its practical applicability, the methodology is systematically applied to railway infrastructure safety—specifically the railroad turnout control system—as a critical case study. The experimental implementation converts operational statecharts of turnout control logic into optimized NuSMV models. Not only did the models remain intact, but the state space was also effectively reduced through the optimization of the hierarchical structure. In the validation phase, the converted model is tested for robustness using the fault injection method, and boundary condition anomalies that are not explicitly stated in the requirement specification are successfully detected. The experimental results show that the validation model generated by this method has improved validation efficiency in the NuSMV tool, which is significantly better than the traditional conversion method. Full article

To address the issue of extra-large structural deformation or strain in infrastructures such as bridges, buildings, railroads, and pipelines during catastrophic events, this study proposes a wide-range fiber Bragg grating (FBG) strain sensor utilizing a snake spring desensitization mechanism to share large parts of the strains. Initially, the axial stiffness of the snake spring desensitization mechanism was derived using the strain energy method, which was applied for stiffness calculation, range determination, and parameter design of the entire structure, where the snake spring and the FBG strain sensor were connected in series. Then, the snake springs were fabricated using 3D printing technology and assembled with the FBG sensor to construct a wide-range strain sensor. The wide-range sensor was subsequently calibrated, achieving a strain range of 10,000 με and a linearity coefficient above 0.9995. Finally, the sensor was installed in a pipeline for testing, yielding favorable results. These results demonstrate that the proposed sensor exhibits a wide strain monitoring range and can be effectively used for real-time structural safety analysis by continuously monitoring localized large structure strains. Full article

Of the 100,000 railroad bridges in the United States, 50% are over 100 years old. Many of these bridges do not meet the minimum vertical clearance standards, making them susceptible to impact from over-height vehicles. The impact can cause structural damage and unwanted disruption to railroad bridge services; rapid notification of the railroad authorities is crucial to ensure that the bridges are safe for continued use and to affect timely repairs. Therefore, researchers have developed approaches to identify these impacts on railroad bridges. Some recent approaches use machine learning to more effectively identify impacts from the sensor data. Typically, the collected sensor data are transmitted to a central location for processing. However, the challenge with this centralized approach is that the transfer of data to a central location can take considerable time, which is undesirable for time-sensitive events, like impact detection, that require a rapid assessment and response to potential damage. To address the challenges posed by the centralized approach, this study develops a framework for edge implementation of machine-learning predictions on wireless smart sensors. Wireless sensors are used because of their ease of installation and lower costs compared to their wired counterparts. The framework is implemented on the Xnode wireless smart sensor platform, thus bringing artificial intelligence models directly to the sensor nodes and eliminating the need to transfer data to a central location for processing. This framework is demonstrated using data obtained from events on a railroad bridge near Chicago; results illustrate the efficacy of the proposed edge computing framework for such time-sensitive structural health monitoring applications. Full article

A steel–concrete composite beam bridge fully exploits the mechanical advantages of the concrete structure and steel structure, and has the advantages of a fast construction speed and large stiffness. It is of certain research value to explore the application of this bridge type in the field of railway bridges. However, with the rapid development of domestic high-speed railway construction, the problem of vibration and noise radiation of high-speed railway bridges caused by train loads is becoming more and more serious. A steel–concrete composite beam bridge combines the tensile characteristics of steel and the compressive characteristics of concrete perfectly. At the same time, it also has the characteristics of a steel bridge and concrete bridge in terms of vibration and noise radiation. This feature makes the study of the vibration and noise of the bridge type more complicated. Therefore, in this paper, the characteristics of vibration and noise radiation of a high-speed railway steel–concrete composite box girder bridge are studied in detail from two aspects: the theoretical basis and a numerical simulation. The main results obtained are as follows: Relying on the idea of vehicle–rail–bridge coupling dynamics, a structural dynamics analysis model of a steel–concrete combined girder bridge for a high-speed railroad was established, and numerical program simulation of the vibration of the vehicle–rail–bridge coupling system was carried out based on the parametric design language of ANSYS 18.0 and the language of MATLAB R2021a, and the structural vibration results were analyzed in both the time domain and frequency domain. By using different time-step loading for the vehicle–rail–bridge coupling vibration analysis, the computational efficiency can be effectively improved under the condition of guaranteeing the accuracy of the result analysis within 100 Hz. Based on the power flow equilibrium equation, a statistical energy method of calculating the high-frequency noise radiation is theoretically derived. Based on the theoretical basis of the statistical energy method, the high-frequency noise in the structure is numerically simulated in the VAONE 2021 software, and the average contribution of the concrete roof plate to the three acoustic field points constructed in this paper is as high as 50%, which is of great significance in the study of noise reduction in steel–concrete composite girders. Full article

Road crashes, although random events, frequently occur on roads. However, certain characteristic infrastructural locations require detailed analysis regarding the frequency of road crashes. This study examines the dynamics of road crashes at characteristic infrastructural locations in Serbia from 2018 to 2022, focusing on bridges, tunnels, railroad crossings, and road work zones. Using data on road crashes from official reports, the analysis includes trends in crash rates, fatalities, injuries, and material damage during the above-mentioned time frame. In addition to the data analysis, 22 experts from the fields of traffic engineering ranked the mentioned characteristic infrastructural locations in terms of road safety. The same questions were asked to six different artificial intelligence software programs. The findings reveal significant variations in crash rates across different infrastructures, with bridges and road work zones having the highest number of crashes. Expert assessment is in line with the analysis of the results, while artificial intelligence gives a completely opposite assessment. Full article

Scour around bridges present a severe threat to the stability of railroad and highway bridges. Scour needs to be monitored to prevent the bridges from becoming damaged. This research studies the feasibility of using green laser for monitoring the scour around candidate railroad and highway bridges. The laboratory experiments that provided the basis for using green laser for underwater mapping are also discussed. The results of the laboratory and field experiments demonstrate the feasibility of using green laser for underwater infrastructure monitoring with limitations on the turbidity of water that affects the penetrability of the laser. This method can be used for scour monitoring around offshore structures in shallow water as well as corrosion monitoring of bridges. Full article

With the rapid development of high-speed railroads and subways, there has been an increasing number of bridge–tunnel overlapping structures. To study the dynamic response characteristics of bridge–tunnel structures under the synergistic effects of the vibration generated by high-speed railway and subway trains, the dynamic response characteristics of a bridge–tunnel structure under single-point vibration loading was analyzed by conducting numerical simulations and model tests, with the frequency response function and peak acceleration as the evaluation indices. The dynamic response characteristics of the overlapping structure under moving vibration loads of the high-speed railway and subway trains were further analyzed. The results showed that the dynamic response of the bridge–tunnel overlapping structure increased with the increase in the frequency under the full frequency domain single-point sweep vibration load. The dynamic response of the tunnel hance near the pile foundation side was significantly greater than the vault and invert. Compared with the effect of high-speed train loads alone, the dynamic response of the bridge–tunnel overlapping structure under the synergistic effects of high-speed railways and subways increased significantly and varied at different locations. This investigation provides theoretical support for the design and construction of bridge–tunnel overlapping structures under the synergistic effects of high-speed railways and subways, contributing to improving engineering quality and safety. Full article

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. Full article

As rail transportation continues to advance, it provides significant convenience to the public. However, the environmental vibration and noise generated during its operation have become major concerns for residents living near rail lines. In response to these concerns, the “Law on the Prevention and Control of Noise Pollution” was promulgated in China, bringing attention to this issue within the rail transportation sector. This review summarizes the regular features observed in environmental vibration and secondary structural noise tests on different sections, including embankment sections, bridge sections, underground railroads and vehicle sections. Furthermore, it introduces several physical models utilized in the study of environmental vibration and secondary structural noise, focusing on three key aspects: excitation sources, propagation paths and the modelling of building structures. This paper also explores the introduction of data-driven models related to big data and artificial intelligence to enhance the accuracy and efficiency of research in this field and provides an overview of commonly used measures to control train-induced environmental vibrations and secondary noise in buildings. These measures are discussed in terms of excitation sources, propagation paths, and receivers, offering insights into effective strategies for mitigating the impact of rail transportation on nearby residents. Finally, this study highlights the primary findings and offers pertinent recommendations. These recommendations include considerations regarding both laboratory and on-site testing procedures, challenges associated with the deployment of data-driven models and key parameters for designing and utilizing low-stiffness fasteners. Full article

Railroads are a critical part of the United States’ transportation sector. Over 40 percent (by weight) of the nation’s freight is transported by rail, and according to the Bureau of Transportation statistics, railroads moved $186.5 billion of freight in 2021. A vital part of the freight network is railroad bridges, with a good number being low-clearance bridges that are prone to impacts from over-height vehicles; such impacts can cause damage to the bridge and lead to unwanted interruption in its usage. Therefore, the detection of impacts from over-height vehicles is critical for the safe operation and maintenance of railroad bridges. While some previous studies have been published regarding bridge impact detection, most approaches utilize more expensive wired sensors, as well as relying on simple threshold-based detection. The challenge is that the use of vibration thresholds may not accurately distinguish between impacts and other events, such as a common train crossing. In this paper, a machine learning approach is developed for accurate impact detection using event-triggered wireless sensors. The neural network is trained with key features which are extracted from event responses collected from two instrumented railroad bridges. The trained model classifies events as impacts, train crossings, or other events. An average classification accuracy of 98.67% is obtained from cross-validation, while the false positive rate is minimal. Finally, a framework for edge classification of events is also proposed and demonstrated using an edge device. Full article