Railway Applications Research Articles

High-Capacity Energy Storage Devices Designed for Use in Railway Applications

High-Capacity Energy Storage Devices Designed for Use in Railway Applications

Explosions of Hydrogen Storages and the Safety Considerations in Hydrogen-Powered Railway Applications—A Review

As one of the most promising clean energy sources, hydrogen power has gradually emerged as a viable alternative to traditional energy sources. However, hydrogen safety remains a significant concern due to the potential for explosions and the associated risks. This review systematically examines hydrogen explosions, with a focus on high-pressure and low-temperature storage, transportation, and usage processes mostly based on the published papers from 2020. The fundamental principles of hydrogen explosions, classifications, and analysis methods, including experimental testing and numerical simulations, are explored. Key factors influencing hydrogen explosions are also discussed. The safety issues of hydrogen power on railway applications are focused, and finally, recommendations are provided for the safe application of hydrogen power in railway transportation, particularly for long-distance travel and heavy-duty freight trains, with an emphasis on storage safety considerations.

Effects of Carbon Type and Composition on the Properties of Carbon-Copper Composite as Pantograph Slide in Railway Application

Carbon-copper composites have wide application prospects as high-speed railway pantograph slides due to the self-lubricating ability of carbon and good conductivity of copper. However, carbon-copper composites produced through powder metallurgy may still encounter challenges, such as poor wettability and lower conductivity. The experimental approach in this work involved the fabrication of carbon-copper composites using the warm compaction method, with different types and proportions of carbon materials, namely local carbon from palm kernel shells (PKS) and graphite. Characterisation and testing of hardness, density, resistivity, transverse rupture strength (TRS), and microstructure of the composites have been conducted. An increase in graphite content was found to improve the electrical conductivity of the carbon-copper composite, while the addition of local carbon has enhanced its hardness. Furthermore, the addition of graphene oxide (GO) as filler has significantly improved the mechanical strength of this composite by up to 61.34%. This research has highlighted the potential of locally sourced carbon for developing advanced pantograph slide materials for railway applications. The findings provided valuable insights into the optimisation of composite compositions to achieve the desired balancebetween electrical conductivity and mechanical performance. These carboncopper composites hold the promise of more efficient and durable pantograph slides, which can contribute to the overall reliability and sustainability of railway systems.

Fabrication and Characterisation of Kenaf Fibre Reinforced Polyamide Biocomposites for Railway Sleeper Applications

Railway passing traffic, speed, and load have significantly increased over the years, prompting industry stakeholders and researchers to seek an alternative sleeper material that can demonstrate its ability to potentially possess higher in-service bending resistance and be environmentally friendly and durable. To address these needs and due to environmental concerns, kenaf-reinforced polyamide has become of great importance. However, they could not be applied as railway track components because of the non-availability of their performance in this regard. In bridging this gap, this paper focused on fabricating and characterising six different formulations of treated kenaf fibre (TKF, 0–50% at 10% loading interval) reinforced polyamide biocomposites for railway sleeper applications. The result showed that the incorporation of TKF influenced the behaviour of the polyamide with respect to its water absorption, load-carrying capacity, and thermal stability. The result further demonstrated that the load-bearing capacity peaked at TKF 40 wt.%, surpassing conventional wooden and concrete sleepers. However, its water absorption (64-days saturation) behaviour increased significantly between 11%–21% as TKF rose from 10–50 wt.%, as expected due to TKF hydrophilic characteristics. On the other hand, TKF thermal stability was hampered beyond approximately 220°C for all TKF percentages. Kenaf fibre-reinforced polyamide biocomposites have demonstrated their potential for railway sleeper applications as their load-bearing capacity exceeded the minimum recommended AREMA specifications. Despite the milestone achieved, water absorption of kenaf fibre remained high. The development of sustainable and effective materials to meet the changing needs of contemporary railway infrastructure is greatly aided by the insights gained from this study.

Experimental Study on the Influence of Crumb Rubber on Temperature Susceptibility of Asphalt for Railway Application in the Tropics

The granular sub-ballast in conventional ballasted trackbed structure, though cheap and easy to construct, requires frequent maintenance, and cannot protect the subgrade against water infiltration. However, asphaltic sub-ballast in asphalt-ballast trackbed can reduce stress on the subgrade and provide a waterproofing layer against water infiltration. Asphalt binder is however, susceptible to temperature fluctuations. The aim of this study therefore is to investigate whether the addition of crumb rubber to asphalt binder could reduce the susceptibility of asphalt to temperature, and thus, improve its performance. The main objective of this research is the addition of four different ratios of crumb rubber; 1, 2, 3, and 4%, of size 0.3 mm to bitumen or asphalt 60/70 grade. The results showed that penetration of the asphalt binder reduced from 66.70 to 59.20 mm at 4% rubber content, implying that the modified asphalt became harder with addition of crumb rubber and thus, can withstand temperatures variations in asphaltic pavements. Softening point, used to test temperature susceptibility of bitumen, increased from 49.10°C to 52.80°C at 4% crumb rubber content, implying that crumb rubber modified asphalt can withstand elevated temperatures in asphaltic pavements, in the tropics. Flashpoint increased from 295.20 to 296.12°C, fire point also increased from 306.50°C to 308.28°C, Specific gravity of the unmodified and crumb rubber-modified asphalt did not change significantly because crumb rubber is not very flammable, Viscosity at 135°C increased from 338.00 to 360.00 cSt at crumb rubber content of 4%, Ductility at 25°C reduced from 122.40 cm to 79.40 cm at 4% crumb rubber content, implying that crumb rubber made asphalt stiffer. This study concludes that crumb rubber can reduce the susceptibility of asphalt to temperature changes.

A new efficient conformal contact model for multibody and railway applications

A new efficient conformal contact model for multibody and railway applications

Using a bonded solid film lubricant to prevent fretting wear in the axle journal bearings of rail vehicles

Fretting degrades the inboard inner ring and the backing ring contact surfaces of axle journal roller bearings used in railway applications. This study attempts to prevent fretting wear between them as well as fretting wear particles from entering the axle bearing interior without introducing new bearing components. It has been reported that coating metallic surfaces with bonded solid film lubricants improves lubricity and wear resistance while reducing fretting wear. To evaluate the impact on fretting wear prevention, a full-size railway axle bearing that was coated a backing ring side face with a bonded solid film lubricant was rotated. The findings demonstrate that applying the bonded solid film lubricant to the backing ring side face does not prevent the axle bearings from fretting. The surface temperature probably exceeds the heat-resistant temperature of the solid film lubricant because of the fretting friction.

Knowledge Graph Completion for High-Speed Railway Turnout Switch Machine Maintenance Based on the Multi-Level KBGC Model

The incompleteness of the existing knowledge graphs in the railway domain creates information gaps, impacting their quality and effectiveness in the operation and maintenance of high-speed railway turnout switch machines. To address this, we propose a multi-layer model (KBGC) that combines KG-BERT, graph attention network (GAT), and Convolutional Embedding Network (ConvE) for knowledge graph completion in railway maintenance. KG-BERT fine-tunes a pre-trained BERT model to extract deep semantic features from entities and relationships, converting them into graph structures. GAT captures key structural relationships between nodes using an attention mechanism, producing enriched semantic and structural embeddings. Finally, ConvE reshapes and convolves these embeddings to learn complex entity interactions, enabling accurate link prediction. Extensive experiments on the HRTOM dataset, containing triplet data from high-speed railway turnout switch machines, demonstrate the model’s effectiveness, achieving an MRR of 50.8% and a Hits@10 of 60.7%. These findings show that the KBGC model significantly improves knowledge graph completion, aiding railway maintenance personnel in decision making and preventive maintenance, and providing new tools for railway maintenance applications.

Magnetic Railway Sleeper Detector

In an ever expanding railway network all around the world, the need for track maintenance grows steadily. Traditionally, one major part of track maintenance is ramming large vibrating steel picks into the gravel between and under railway sleepers to compress the gravel and generate a safe substructure. Even today, maintenance personnel still have to manually locate the sleepers if they cannot be detected by computer vision systems or visually by the operator. Here we developed a first of its kind magnetic sleeper detector, even able to find sleepers, buried in gravel, undetectable by vision based systems. Our approach of magnetic detection is based on a DC magnetic field excitation and a detector moving with respect to the rail system, including the sleepers and fasteners for mounting the rails. Due to railway application constraints a large air gap between the sensor and the sleeper structure is required, which significantly complicates the magnetic sensing task for robust sleeper detection. The design and optimization of the magnetic circuit was based on extensive 3D simulation studies to ensure highest possible variation in magnetic flux density at the sensor locations for absence and presence of a sleeper. Furthermore, a low noise and high sensitivity electronic circuit has been realized to cope with sensor signal offsets from unknown or changing sensor orientations with respect to the earth’s magnetic field, or magnetic interferences from other trains potentially passing by during active measurements. Since we only want to detect sleepers in close vicinity of the moving sensor system, digital signal processing of the acquired signals can easily compensate for disturbing slowly changing or static field components within real world application scenarios. We demonstrate that magnetic detection of even buried sleepers on railway tracks is possible for distances of up to 172 mm between the sensor and the sleeper. This enables an even higher level of railway maintenance automation previously impossible in certain scenarios.

Advancements in railway noise simulation: assessment of tools for virtual validation

In pursuit of more efficient and cost-effective measurement campaigns, the railway industry is embracing the prospect of virtual validation based on simulations. The primary obstacle lies in the need for noise simulation tools capable of accurately replicating complex sources, installation effects, noise propagation, ground reflection and, for some cases, the diffraction in the different train surfaces. This paper presents insights derived from European project Shift2Rail S2R-CFM-CCA-01-2019 Energy and Noise & Vibration WP6, concentrating on the validation and enhancement of two exterior noise simulation tools, tailored for railway applications. The paper covers four reference cases, simulating exterior noise at standstill with diverse noise sources and varying source locations and noise emission (i.e. electrical noise, cooling, etc.). A correlation with previously conducted measurements at typical receiver locations (7.5 meters from the track centerline) is carried out. The measurements were conducted in a "controlled" configuration, isolating as much as possible the analyzed noise source and gathering all the needed information about the ground and train geometry. The evaluation between measurements and simulations is done against a global and a 1/3rd octave band criteria with successful results. Finally, key features essential for achieving more accurate simulations are listed.

Effects of ultrasonic vibration on residual stress distribution and local mechanical properties of AA6061/Ti6Al4V dissimilar joints by resistance spot welding

The joining of dissimilar titanium and aluminum alloys has potential applications in railway and aerospace industries, owing to substantial weight reduction and better economic viability. In this study, the residual stress distribution and local mechanical performance of ultrasonic-assisted resistance spot welding (UaRSW) welds were investigated. The welding current, welding time, and electrode force of the RSW process were set as 9.0 kA, 350 ms, and 1.0 kN respectively, and the frequency and power of ultrasonic vibration were 20 kHz and 800 W. The residual stress was evaluated by X-ray diffraction (XRD) method and numerical simulation, and these methods showed a reasonable match. There was tensile residual stress distributed on RSW welds and UaRSW welds, but the value of residual stress was reduced by about 30% at welding nugget and 20% at heat affected zone (HAZ) with the ultrasonic vibration, the reduction of residual stress in UaRSW welds was attributed to the more uniform temperature distribution and lower plastic deformation resistant of AA6061. The welding peak temperature was decreased from 1673.4 °C to 1584.2 °C with the ultrasonic vibration, resulted from the modified Al/Ti contact surface and reduced contact resistance. The miniature tensile test results showed the improvement of mechanical performance by ultrasonic vibration. The maximum load of welding nugget region increased from 19.6 N to 22.3 N, and the elongation obtained 10% increase. This hybrid welding technique shows a potential to improve the quality of welds with ensured efficiency, which is also simple to realize automation in the manufacturing industry.

Experimental investigation into friction stir welding of AA6061-T6 and magnesium AZ31B alloy using copper backing plate

Aluminium-magnesium alloys are lightweight and possess superior properties, making them ideal for applications in aerospace, railway, automotive, and marine structures. However, these alloys are challenging to fabricate using traditional fusion welding due to various metallurgical issues. This study investigates the feasibility of joining 3 mm thick dissimilar alloys of aluminium AA6061-T6 and magnesium AZ31B using the friction stir welding (FSW) process with copper as a backing plate. The effects of FSW process parameters, including tool rotational speed (380, 545, 765 rpm), weld speed (20, 31.5, 50 mm min−1), and tilt angle (1°, 2°, 3°), on tensile properties were examined using Taguchi-based grey relational analysis. Temperatures were recorded during the FSW process under different conditions on both sides of the joint. The highest tensile strength of 130.72 MPa, with a joint efficiency of 67.85%, was achieved at a tool rotational speed of 765 rpm, a welding speed of 50 mm min−1, and a tilt angle of 2°. Analysis of variance (ANOVA) for the grey relational grade indicated that the tilt angle had the highest percentage contribution of 43.60%. This study demonstrates the significant influence of FSW parameters on the mechanical properties of aluminium-magnesium joints and highlights the optimal conditions for achieving high joint strength and efficiency.

Experimental and numerical investigation of the track structure elasticity induced by resilient fastener on vehicle-track interaction and train running stability

The resilient fastener slab track (RFS track) has found extensive application in urban railways, effectively mitigating vibration and noise resulting from train operations. However, the structure elasticity of the RFS track is higher than the normal slab track (NS track), which can affect train running stability and cause abnormal vibration phenomenon. This paper explores the track structure elasticity on vehicle-track interaction and train running stability through experimental tests and numerical simulations. The vibrational properties of the RFS track and the NS track are obtained through field tests. A 3D metro vehicle-track coupled dynamics model is developed and utilized to simulate the dynamic performance of metro vehicles moving on different track structures. The impact of track structure parameters upon the vehicle-track interaction and train running stability are discussed. The findings indicate that the track structure elasticity can reduce train hunting stability and cause abnormal vibration phenomena in metro vehicles under certain conditions. The reasonable matching of the fastener lateral and vertical stiffness can not only accomplish vibration attenuation but also minimize the impact on train running stability. In addition, the rail surface wear and track gauge variation also exert influence on the running stability and dynamic performances of metro vehicles.

Specifics of Data Collection and Data Processing during Formation of RailVista Dataset for Machine Learning- and Deep Learning-Based Applications.

This paper presents the methodology and outcomes of creating the Rail Vista dataset, designed for detecting defects on railway tracks using machine and deep learning techniques. The dataset comprises 200,000 high-resolution images categorized into 19 distinct classes covering various railway infrastructure defects. The data collection involved a meticulous process including complex image capture methods, distortion techniques for data enrichment, and secure storage in a data warehouse using efficient binary file formats. This structured dataset facilitates effective training of machine/deep learning models, enhancing automated defect detection systems in railway safety and maintenance applications. The study underscores the critical role of high-quality datasets in advancing machine learning applications within the railway domain, highlighting future prospects for improving safety and reliability through automated recognition technologies.

Effect of Graphene Quantum Dots (GQDs) on the mechanical, dynamic, and durability properties of concrete

Addressing ecological concerns stemming from concrete usage is paramount, prompting exploration into additives for mitigation. Graphene quantum dots (GQDs) have been recognized for their potential to improve the mechanical attributes of cement composites. Additionally, the electrochemical reduction of a saturated solution of carbon dioxide (CO2) and monoethanolamine (CO2-MEA) effectively removes CO2 from the atmosphere. This study delves into the influence of GQDs on the mechanical and durability aspects of concrete. It is noted that the control mix of concrete without GQDs was specifically designed for concrete railway sleepers. Varied proportions of GQDs, ranging from 0.3 % to 1.2 % at 0.3 % increments, were incorporated to assess their impact on fresh and hardened concrete properties. Mechanical properties such as compressive strength, splitting tensile strength, flexural strength, and dynamic properties were evaluated. Durability assessments encompassing water absorption and chloride ion penetration were conducted. Microstructural analysis via Field Emission Scanning Electron Microscopy (FESEM) imaging and Energy-dispersive X-ray spectroscopy (EDS) elucidated the concrete's internal composition. Notably, an optimal GQDs percentage of 0.3 % was observed, signifying its efficacy in enhancing the performance of concrete. When 0.3 % of GQDs was added to concrete, compressive strength, split tensile strength, and flexural strength were enhanced by 10.8 %, 23 %, and 11 % respectively. The incorporation of GQDs resulted in a notable improvement in the fundamental frequencies and dynamic modulus of elasticity. Concurrently, a decrease in the damping ratio was observed for specimens containing GQDs. Additionally, the porosity and chloride penetration depth were lower by 6 % and 30 % for specimens with 0.3 % GQDs. The improvement in workability, mechanical, and dynamic properties of concrete, along with reducing CO2 from the atmosphere, makes GQDs an ideal eco-friendly material. This study is the first to open new pathways for the development of construction materials that are not only structurally superior but also environmentally responsible, marking a significant step forward in the field of civil engineering materials, especially in railway applications.

Effect of cooling rate in the mid-temperature region on fatigue crack propagation rate of bainitic steel

Controlling continuous cooling is an important means to control the most important mechanical properties of bainitic steel for frogs in railroad applications. In this paper, a bainitic steel for railway frogs is taken as the research object. By designing different cooling rates in the bainitic transformation medium temperature region, the effect of cooling rate on fatigue crack propagation rate was studied. The results show the sample of 4 °C/s cooling rate exhibits higher strength and impact toughness, while the crack propagation rate near the threshold is significantly lower and the threshold is relatively higher at 0.1 °C/s cooling rate. This is related to the fact that more massive blocky retained austenite and coarse microstructure in the sample at 0.1 °C/s cooling rate are more favorable to the occurrence of crack closure effect, especially in the near-threshold region. The fatigue crack propagation rate of the tested steel in the stable propagation region at 4 °C/s cooling rate is slightly higher than that at 0.1 °C/s. This is related to its complex interface distribution characteristics. However, with the increase of Δ K, the tested steel at 0.1 °C/s cooling rate tends to preferentially fail, which is related to its poor toughness.

Railway Infrastructure Cybersecurity: An Overview

The railway infrastructure constitutes a type of operational technology (OT)-based critical infrastructure, which is expected to work 24x7, 365 days a year, and where the life expectancy of operational equipment often exceeds 30 years. In this domain, an operational anomaly compromising the OT system can cause a train accident or interrupt traffic, with potentially significant impact in terms of business as well as for passenger safety. Due to their relevance, railways are strategic assets of national interest and, consequently, targets of interest for cybercriminals and cyberwarfare activities. For instance, service interruptions may trigger ripple effects resulting in product shortages and widespread supply chain disruptions, with severe impacts for both the economy and national security. In a bid to optimise and streamline operations. the railway industry has recently started taking a series of significant steps towards digitization, with infrastructures experiencing a significant paradigm shift which, for instance, makes it possible to have centralised interlockings and Radio Block Centre (RBC) for an entire country, with geographical redundancy, ensuring the utmost availability and punctuality by moving the control logic to the cloud. Nevertheless, these developments must always be carried on within the scope of established cybersecurity standards and frameworks. This paper presents an analysis of the state of the art on railway cybersecurity, focused on the existing solutions based on the application of the CENELEC “Technical specification 50701 - Railway Application – Cybersecurity”, which is currently the latest European specification addressing railways, being designed to help suppliers, integrators, and operators to implement a cybersecurity risk assessment plan, the necessary controls, and the management of the complete system life cycle. Special attention will be paid to the conduit between the rail signal interlocking system, that controls the line signalling, and the Automatic Train Supervision (ATS) that runs in the Operational Control Centre (OCC), as this has been identified by the European Union Agency for Cybersecurity (ENISA) as one of the most critical systems identified by the operators of essential services.

Review of Fault Diagnosis Methods for Induction Machines in Railway Traction Applications

Induction motors make up approximately 80% of the electric motors in the railway sector due to their robustness, high efficiency, and low maintenance cost. Nevertheless, these motors are subject to failures which can lead to costly downtime and service interruptions. In recent years, there has been a growing interest in developing fault diagnosis systems for railway traction motors using advanced non-invasive detection and data analysis techniques. Implementing these methods in railway applications can prove challenging due to variable speed and low-load operating conditions, as well as the use of inverter-fed motor drives. This comprehensive review paper summarizes general methods of fault diagnosis for induction machines. It details the faults seen in induction motors, the most relevant signals measured for fault detection, the signal processing techniques for fault extraction as well as some classification algorithms for diagnosis purposes. By giving the advantages and drawbacks of each technique, it helps select the appropriate method that could address the challenges of railway applications.

Lightweight railroad semantic segmentation network and distance estimation for railroad Unmanned aerial vehicle images

Derailments significantly harm railroads in terms of severity and fatality rates. Manually monitoring railway tracks is a tedious and often insufficient task to prevent derailment accidents. This necessitates the development of an automated monitoring system to oversee the condition of railway tracks. In the foreseeable future, Unmanned Aerial Vehicles (UAVs), artificial intelligence, and computer vision will play a crucial role in periodically assessing the railway environment to ensure passenger safety. This paper proposes a lightweight and efficient railroad semantic segmentation network (Lite-RSNet), which segments real-time aerial railroad images into rails, gauges, and backgrounds. The segmented regions then compute the distance between rails and obstacles, identifying potential derailment hazards in railroad applications. Lite-RSNet incorporates a multi-level feature fusion framework that includes a residual layer, a multi-head attention layer, a Concurrent Spatial and Channel Squeeze Excitation (CSSE) block, and a Convolutional Block Attention Module (CBAM). The designed approach enhances onboard processing efficiency by streamlining the model to use fewer parameters and reduce storage demands. Performance assessment of the model utilized the Rail Segmentation Dataset (RSD), which consists of high-resolution, low-altitude aerial photographs of Indian railroads. The Lite-RSNet model outperforms current leading methods, maintaining a lean structure with only 6 million parameters and achieving notable metrics of 0.971 for the Dice Coefficient (DC) and 0.947 for the Jaccard Index (JI) on the test dataset. Furthermore, distance estimation between an obstacle and rail has been implemented using image processing techniques as an additional work of this proposal to know about the caution of an obstacle.

Piezo stack energy harvesters with protection components for railway applications

Piezo stack energy harvesting from railway vibrations shows substantial potential for powering wireless sensor networks responsible for monitoring railway infrastructure. Nevertheless, assuring the safety and durability of these energy harvesters in the condition of the dynamically fluctuating railway vibrations remains a considerable challenge. In this paper, we present two innovative protection methods designed for piezo stack energy harvesters with a frequency up-conversion mechanism. These methods involve the incorporation of ring-type and circular stoppers within the resonant system and the utilisation of proposed impact protection components within the impact system. Two distinct harvesters incorporating the proposed protection components, Harvester Types I and II, are designed to align with their respective operating acceleration targets, which are determined based on the amplitudes of railway vibration acceleration. Finite element modelling is used to guide the design process, involving the evaluation and selection of various design parameters aligned with the acceleration target and stress limits. The protection mechanisms’ effectiveness and impact on energy harvesting performance have been validated through experimental testing under measured rail vibration signals, and their performance has been further assessed through stress analyses. Harvester Type I operates seamlessly within a 5 g threshold, effectively mitigating the increase in maximum output acceleration and stress beyond this limit. In contrast, Harvester Type II efficiently dissipates excess energy, enabling the harvester to operate at a 15 g acceleration while reducing the rate of acceleration and stress growth. The results demonstrate that both proposed harvesters provide effective protection from unexpected railway vibration overloads. This research makes a significant impact on the practical, real-world implementation of piezo stack energy harvesters operating within the dynamic environment of railway vibrations.