Search Results (186)

The composite materials industry is increasingly seeking sustainable alternatives to mitigate the environmental impact of end-of-life materials. As a result, many sectors are transitioning toward bio-based or partially bio-based matrices (e.g., epoxy resins) to preserve material properties while improving sustainability. The transportation sector, in particular, demands materials that meet stringent mechanical and fire resistance standards. In this study, various epoxy systems with bio-based and/or recyclable content were investigated, along with renewable additives designed to enhance fire resistance through their functional groups and chemical structure. The research focused on developing formulations compatible with Sheet Moulding Compound (SMC) technology, which is widely used in transportation applications. Through extensive testing, materials with high bio-based content were successfully developed, exhibiting competitive mechanical properties and compliance with key fire safety requirements of the railway sector, as per the EN 45545-2 standard. Full article

A wheel flat is the most common fault of a railway freight car, a type of complex transport equipment. A wheel flat will cause continuous regular impact on the rail, damage the rail and the railway structure, affecting the safety and stability of rail transport. This article studied the relationship between wheel flats and wheel–rail impacts using multi-body dynamics simulation through SIMPACK and, through a field test, validates the detection of a flat wheel. The results show that using the simulation method can obtain similar data to the measured wheel–rail force in the wayside detection device. The simulation data show that the data collected by 14 shear vertical force acquisition channels can completely cover the wheel surface of the heavy-duty railway 840 mm diameter wheel. According to the flat length-speed-impact diagram, the mapping relationship can be fitted using polynomial regression. Based on the measured wheel–rail impact forces, the size of wheel flats can then be deduced from this established mapping relationship. Through a field test, the detection method has been validated. Full article

As a key transportation infrastructure, it is of great significance to ensure the seismic safety of the high-speed railway hub station. Taking Changde high-speed railway hub station as background, a comprehensive 3D numerical model of the high-speed railway station structure is proposed to consider the engineering geological characteristics of the site, soil nonlinearity, and pile-soil interactions. The results show that the hub station structural system, considering pile-soil interaction, presents the ‘soft-upper-rigid-down’ characteristics as a whole, and the natural vibration is lower than that of the station structure with a rigid foundation assumption. Under the action of three strong seismic motions, the nonlinear site seismic effect is significant, the surface acceleration is significantly enlarged, and decreases with the buried depth. The interaction between pile and soil is related to the nonlinear seismic effect of the site, which deforms together to resist the foundation deformation caused by the strong earthquake motions, and the depth range affected by the interaction between the two increases with the increase of the intensity of earthquake motion. Among the three kinds of input earthquake motions, the predominant frequency of the Kobe earthquake is the closest to the natural vibration of the station structure system, followed by the El Centro earthquake. Moreover, the structures above the foundation of the high-speed railway hub station structural system are more sensitive to the spectral characteristics of Taft waves and El Centro waves compared to the site soil. This is also the main innovation point of this study. The existence of the roof leads to the gradual amplification of the seismic response of the station frame structure with height, and the seismic response amplification at the connection between the roof and the frame structure is the largest. The maximum story drift angle at the top floor of the station structure is also greater than that at the bottom floor. Full article

The safe transport of cylindrical loads such as metal, paper, or polymer rollers requires specialized securing structures that address the complex dynamic forces encountered during rail movement. This paper presents a structured methodology for the design and verification of such securing systems, combining theoretical analysis, standardized load models, and numerical simulations. The method includes load calculations based on EN 12195-1:2010, EN 15551, and Eurocode 1, and validation through finite element modeling in Ansys Workbench. The proposed structure ensures stability under static and dynamic loads, including acceleration, braking, turning, and wind forces, while optimizing wagon space utilization. Simulation results confirm that the design meets strength and safety criteria without exceeding material stress limits, offering a reliable solution for the secure transport of cylindrical rollers. Full article

This study deals with the problem of uneven wear of brake pads of wagons caused by a set of structural, dynamic, technological and operational factors. It has been found that an uneven distribution of the brake pad pressure force leads to higher maintenance costs and lower braking efficiency. The main causes of uneven wear are worn kinetostatic units, differences in the geometric parameters of pads, and imperfections in the lever transmission design. A method for optimizing the distribution of the pressure force using weight coefficients and the Lagrange function has been developed; it reduces the uneven wear of brake pads to 8–10% compared to that of a typical wagon bogie brake system, which is 20–35%. The experiments conducted have shown that for a mileage of 74,400 km and with the air distributor in empty mode, the wear of the pads is 19.6–28 mm, while in the loaded mode it amounts to 27.53–38.04 mm. The stress state of brake pads was determined with consideration of the weight coefficients. It was found that for abnormal wear of brake pads, their strength is not observed. The strength of the wheel when interacting with an abnormally worn pad has also been assessed. The resulting stresses are 1.5% higher than those that occur when the wheel interacts with the pad with nominal dimensions. The results of the research will contribute to the database of developments to be used for designing of modern structures of tribotechnical pairs of rolling stock and increasing the efficiency of railway transport. Full article

The digital transformation of the railway industry is necessary for addressing growing challenges and advancing its sustainable development. Digital technologies include Automatic Train Operation (ATO) and Remote Train Control (RTC), which offer opportunities to potentially optimize operations and enhance safety. Both technologies, however, could pose significant challenges that need to be addressed in order to capture the anticipated benefits in an urban public street environment. This study thus bridges the gap between theory and practice by exploring the projected benefits and challenges of implementing RTC and ATO through a case study of a European public transport operator deploying these technologies in tramway operations. Employing a case study methodology, the research draws on 44 semi-structured interviews with stakeholders from the operator and its supplier. The findings highlight significant anticipated benefits, including increased productivity, improved safety, and enhanced sustainability. Yet, prospective challenges such as regulatory hurdles, technical complexities, and organizational changes pose barriers to implementation. Key obstacles include ensuring robust connectivity, addressing cybersecurity concerns, and managing workforce transitions. This study underscores the importance of collaborative approaches, stakeholder engagement, and incremental deployment to mitigate risks and maximize the impact of automation technologies. By providing actionable insights into the practical adoption of RTC and ATO, this research supports the development of advanced urban transport systems. Full article

Railway safety inspections, a critical component of modern transportation systems, face significant challenges from adverse weather conditions, like fog and rain, which degrade image quality and compromise inspection accuracy. To address this limitation, we propose a novel deep learning-based image dehazing algorithm optimized for outdoor railway environments. Our method integrates adaptive high-pass filtering and bilateral grid processing during the feature extraction phase to enhance detail preservation while maintaining computational efficiency. The framework uniquely combines RGB color channels with atmospheric brightness channels to disentangle environmental interference from critical structural information, ensuring balanced restoration across all spectral components. A dual-attention mechanism (channel and spatial attention modules) is incorporated during feature fusion to dynamically prioritize haze-relevant regions and suppress weather-induced artifacts. Comprehensive evaluations demonstrate the algorithm’s superior performance: On the SOTS-Outdoor benchmark, it achieves state-of-the-art PSNR (35.27) and SSIM (0.9869) scores. When tested on a specialized railway inspection dataset containing 12,840 fog-affected track images, the method attains a PSNR of 30.41 and SSIM of 0.9511, with the SSIM being marginally lower (0.0017) than DeHamer while outperforming other comparative methods in perceptual clarity. Quantitative and qualitative analyses confirm that our approach effectively restores critical infrastructure details obscured by atmospheric particles, improving defect detection accuracy by 18.6 percent compared to non-processed images in simulated inspection scenarios. This work establishes a robust solution for weather-resilient railway monitoring systems, demonstrating practical value for automated transportation safety applications. Full article

One of the main challenges in the operation of electric traction vehicles is ensuring safety and operational reliability. To ensure the safety of railway traffic, vehicles must undergo a series of tests related to the investigation of disturbances generated, among others, in the return current to the mains. This problem is further complicated by the inability to perform such measurements under laboratory conditions. The implementation of tests under real conditions determines the appearance of additional potential interference sources, from power sources to improper interactions between current collectors and the overhead contact system, and it requires strict compliance with regulatory standards and the implementation of standardized testing procedures. This article presents issues related to the investigation and analysis of the electromagnetic compatibility of rolling stock with train detection systems using track circuits. The aim of these tests is to determine the harmonic components in the traction current in relation to the permissible levels specified in the latest editions of the European Railway Agency—ERA/ERTMS/033281 version 5.0 documents and Annex S-02 to the List of the President of the Office of Rail Transport. The measurement methodology and test procedures are presented in detail with respect to current legal requirements. Full article

In today’s world, everything changes at lightning speed, making what is relevant today potentially obsolete tomorrow. This author’s scientific article addresses the issues of energy resilience and cybersecurity in railway signaling. A new proposal based on artificial intelligence is made to improve the fault tolerance of rail transport signaling infrastructure by ensuring increased energy efficiency and detecting cyber-attacks in real time. A linearly coupled neural network model was designed and implemented in a railway signaling simulation to simultaneously track the energy characteristics of signaling and detect abnormal behavior. The authors’ model was validated based on MATLAB(24.2.0.2863752 (R2024b) Update 5) simulations of a real double-track railway line under normal operating conditions and in a ransomware cyber-attack scenario. The AI simulation model correctly predicted the resilience of the signaling system, achieving an average absolute error of 0.0331 in predicting the fundamental performance indicator, and successfully identified an upcoming cyber-attack 20 min before the incident. This study demonstrates the promising architecture of the AI-based signaling system, which provides a significant increase in resilience to emergency situations in relation to power supply and cyber-attacks. By optimizing the signaling infrastructure with AI, it is possible to ensure safe and continuous movement of trains, including emergency situations, representing a promising approach to improving the resilience and safety of railways. Full article

With the development of railway transportation, diversified demands for track structures require the design methods to be safer, more flexible and efficient. At present, the limit state method is regarded as a more scientific design method compared to the allowable stress method, but its optimization effects await further research. Taking a new type of prefabricated track slab as an example, the differences between the two methods are deeply analyzed using finite element simulation and formula calculation. The development prospect for the track design methods is proposed, providing reference for new structures. The results show the following: (1) There are significant differences in the calculation principles between the two methods. Unlike the single safety factor K of the allowable stress method, the partial factors of the limit state method make it more reasonable. (2) The working conditions of different train speeds and temperature gradients are the main factors influencing the design results, and the latter plays a main control role. (3) Under current specification, the reinforcement and slab thickness can be reduced by approximately 6.5% and 3.4%, respectively, according to the limit state method, but the values its coefficient still need to be studied further to achieve efficiency. Full article

With the high-density operations of high-speed trains, predicting the health status of core components such as traction motors is crucial for enhancing the safety and sustainability of trains. Currently, traditional maintenance mechanisms such as periodic inspections and fixed-threshold alarm systems are hindered by delayed abnormality detection and inadequate real-time responsiveness. This paper proposes a dynamic prediction method for traction motor states based on an Online Gated Recurrent Unit (OGRU), which considers various influencing factors and updates model parameters in real-time. Experimental results demonstrate that the online prediction model significantly reduces the $RMSE$ compared to offline methods and exhibits increased prediction stability under different conditions and step sizes. Notably, it decreases computational time by 23.3% relative to the Online Long Short-Term Memory (OLSTM) approach. The proposed method enhances preventive maintenance strategies, optimizes resource utilization, extends equipment lifespan, and reduces costs, thereby making a substantial contribution to the sustainable operation of high-speed railways. By improving energy efficiency, safety, and economic viability, this approach supports a transition toward greener rail transportation. Based on this study, the developed method can facilitate real-time maintenance decision-making, enabling the intelligent operation and maintenance of high-speed trains. Full article

Transport networks are crucial for economic growth, yet their sustainability is increasingly threatened by natural hazards. Recent floods in Italy have highlighted the vulnerability of rail and road infrastructure, causing severe damage and economic losses. The Gargano Promontory in northern Apulia has experienced frequent hydrogeological disruptions over the past decade, significantly affecting bridges and the railway network managed by Ferrovie del Gargano s.r.l. (FdG). However, structural interventions are complex, time-consuming, costly, and involve certain risks. To enhance sustainability and comply with railway safety regulations, FdG has adopted non-structural measures to improve hydrogeological risk classification and management. Despite the prevalence of flood events, the existing literature often overlooks crucial technical aspects, which this study addresses. The HYD.RAIL (HYDraulic Risk Assessment for Infrastructure and Lane) research project aims to improve transport infrastructure resilience by refining hydraulic risk assessments and introducing new classification parameters. HYD.RAIL employs a multicriteria approach, integrating parameters defined in collaboration with railway professionals. This paper presents the initial framework, offering a methodology to identify, classify, and manage hydrogeological risks in transportation infrastructure. Compared to standard methods, which lack detailed risk classification, HYD.RAIL enables more precise flood risk mapping. For example, high-risk points were reduced from 37 to 6 locations on Line 1 and from 134 to 50 on Line 2 using HYD.RAIL. This approach enhances flood risk management efficiency, providing railway operators with a more accurate understanding of infrastructure vulnerabilities. Full article

Railway transportation is a critical component of global infrastructure which plays a significant role in ensuring the safe movement of goods and people. In desert environments, the effectiveness of railway transportation heavily relies on addressing key challenges such as shifting sand, migrating dunes, wind erosion, and sand deposition, which can disrupt operations and increase maintenance costs. To mitigate the significant threats posed by windblown sand to railway safety along the Lanzhou-Xinjiang High-Speed Railway, the technique of double rows of sand fences constructed from concrete columns and plates has been applied to the windward side of the railway. These structures are designed to reduce wind speed and capture moving sand, protecting the rail infrastructure. These fences reduce wind velocity on their leeward sides by 78% and 87% for the first and second rows, respectively. Additionally, due to the large openings in the fences, the sand-trapping efficiencies are 72% for the first row and 63% for the second. The effective shelter distance of the fence is ten times its height. However, advanced technologies like geographic information systems (GIS), geothermal energy solutions, and sustainable infrastructure practices are increasingly integrated into railway transportation to mitigate these risks and enhance safety and reliability. For the Etihad Railway, GIS techniques were utilized to identify areas vulnerable to sand accumulation and validate the substantial benefits of sand fences. Notably, a 40% reduction in wind speed and a significant 74% decrease in sand flux were observed post-installation, underscoring the effectiveness of these structures in disrupting sand mobility. Specifically, wind speed after fence installation was reduced by 40%. The threshold velocity for sand transport was approximately 0.206 m/s. The sand flux before fence installation was 19.95 kg/m²/s, reduced to 5.175 kg/m²/s after fence installation, marking a 74% reduction. The sand deposition behind the sand fence over a 500 m section was around 7387.5 kg/s. This demonstrates the significant role that sand fences play in reducing wind-driven sand transport, thus protecting the Etihad Railway from sand accumulation, and maintaining operational safety. Full article

Currently, there are many gaps in the research on the safety of hydrogen-powered trains, and the hazardous points vary across different scenarios. It is necessary to conduct safety analysis for various scenarios in order to develop effective accident response strategies. Considering the implementation of hydrogen power in the rail transport sector, this paper reviews the development status of hydrogen-powered trains and the hydrogen leak hazard chain. Based on the literature and industry data, a thorough analysis is conducted on the challenges faced by hydrogen-powered trains in the scenario of electrified railways, tunnels, train stations, hydrogen refueling stations, and garages. Existing railway facilities are not ready to deal with accidental hydrogen leakage, and the promotion of hydrogen-powered trains needs to be cautious. Full article

As a critical fastener connecting steel rails, fish-tail bolts ensure the safety of railway transportation. To improve the efficiency of fish-tail bolt loosening detection, this paper proposes a computer vision-based method for detecting fish-tail bolt looseness under tilted perspectives. The method first identifies bolt positions and coordinates of corner points on rail clamp edges through object detection and key point detection. Then, considering diverse rail clamp dimensions and combining with bolt positions, it employs dual perspective transformations for image rectification. Finally, utilizing the Lightweight OpenPose network, angle recognition of key bolt edges is achieved through Gaussian ring-shaped smooth labels, with loosening determination made by comparing angular variations across temporal frames. In experimental validation, tests were first conducted on a public dial-reading dataset for pointer angle recognition, showing a minimum average error of only 0.8°, which verifies the algorithm’s feasibility. Subsequently, based on fish-tail bolt images captured under various tilted perspectives, we constructed a self-made dataset of bolt key edges and performed loosening detection experiments. For bolt images in boundary postures, after rotation preprocessing, the average detection error was reduced to 0.7°. When the loosening threshold was set to 2.1°, the detection accuracy reached 97%. Experimental results indicate that the proposed method effectively identifies fish bolt loosening, providing crucial technical reference for railway safety maintenance. Full article