Railway System Research Articles

Energy Recovering in DC Railway Systems

Energy Recovering in DC Railway Systems

Accident Prevention of BOXN Wagon Train

The safety and efficiency of railway freight transportation are critical to the functioning of many national economies, and India is no exception. BOXN wagons, widely used in the Indian railway system for transporting heavy goods such as coal, minerals, and other bulk materials, are essential for supporting industries across the country. However, due to their size, weight, and the volume of cargo they carry, these wagons are prone to accidents if not properly managed. Accidents involving BOXN trains can result in severe consequences, including loss of life, damage to property, and environmental degradation. One of the biggest and most significant industries in the world is the Indian goods railway sector. It is essential for the transportation of materials and goods across the nation. Indian Railways seeks to shorten commute times by boosting the average freight train speed efficiently from 22 mph to 50 mph. The adoption of new technologies is anticipated to have positive effects on the Indian goods railway sector as well. Smart Innovations, for instance, smart goods cars and digital signaling can contribute to reducing train accidents and help to increase railroad productivity using smart mobility.

Performance evaluation of a racetrack high temperature superconductor winding in an HTS levitation platform

Abstract High temperature superconducting (HTS) is a key technology of next generation high-speed railway systems, which guarantees high current and highly efficient traction power supply. HTS devices can reduce system weight and thus improve loads of vehicles. On high-speed maglev trains, HTS windings wound by second-generation (2G) HTS tapes play an important role in suspension and traction. However, in complex ferromagnetic environments, the performances of windings are notably influenced by the varying magnetic fields. In this paper, a new maglev platform is designed and comprised of a winding of six racetrack HTS coils, an E shape iron core and a magnetic guide rail. The air core structure of the winding is modeled，tested and the electromagnetic characteristics are analyzed for three dimensional (3D) finite element analysis of the platform. An A formulation is used to calculate magnetic vectors A and infer magnetic flux densities and current densities for the structures. After the winding is installed on the iron core and the magnetic guide rail is suspended above the iron core, the air gap between the iron core and the rail is varied from 0 mm to 20 mm in models and experiments. The magnetic fields, critical currents and losses of the winding in cases of the air core and the iron core conditions are used for analysis. The comparison between the air core and the iron core conditions confirms the reliability of the proposed models. This study provides means for analysis of complex superconducting maglev systems.

Detection And Accident Prevention Of Animals in Railway Track Using AI And IoT

Railway is the most widespread and welcoming transportation system of most of the large cities in the world. The real-time observation and control methods proposed in this research are based on the Internet of Things and function autonomously without external intervention. There are several ways that IoT might improve the railway system. Railway automation has the potential to revolutionize existing legacy systems and significantly reduce railway-related incidents. The proposed method for identifying and recognizing animals and humans has been tried and refined. Implement real-time control and automated monitoring of different parameters relevant to the railway. Build a fully automatic process that reduces human involvement and retains energy.

Analysis of the Application and Prospects of Intelligent Technology in Sustainable Railway Operations

With the rapid development of technology, intelligent technology plays an increasingly important role in the sustainable operation of railways. This paper explores the application and prospects of intelligent technology in sustainable railway operations, emphasizing its key roles in enhancing operational efficiency, strengthening safety assurance, optimizing passenger experience, and promoting environmental protection and energy conservation. Through intelligent dispatching, real-time monitoring, big data prediction, personalized services, and mobile ticketing technologies, the railway system achieves efficient resource allocation and service innovation. The intelligent transformation of railways demonstrates significant economic and social benefits, contributing to emission reduction targets and sustainable development. Future efforts should focus on strengthening top-level design, technological innovation, standard construction, and network security to advance the intelligent railway process and co-create a new era of smart, green, and efficient railway transportation.

Organizational foundations of the post-war restoration of the railway healthcare system in the territories of the Central Chernozem regions (1945‒1959)

Organizational foundations of the post-war restoration of the railway healthcare system in the territories of the Central Chernozem regions (1945‒1959)

Signal processing for enhancing railway communication by integrating deep learning and adaptive equalization techniques.

With the increasing amount of data in railway communication system, the conventional wireless high-frequency communication technology cannot meet the requirements of modern communication and needs to be improved. In order to meet the requirements of high-speed signal processing, a high-speed communication signal processing method based on visible light is developed and studied. This method combines the adaptive equalization algorithm with deep learning and is applied to railway communication signal processing. In this research, the wavelength division multiplexing (WDM) and orthogonal frequency division multiplexing (OFDM) techniques are used, and fuzzy C equalization algorithm is used to softly divide the received signals, reduce signal distortion and interference suppression. The experimental results showed that increasing the step size could reduce the equalization effect, while increasing the modulation parameter will increase the bit error rate. Through deep learning to achieve channel equalization, visible light communication could effectively mitigate multi-path transmission and reflection interference, thereby reducing the bit error rate to the level of 0.0001. Under various signal-to-noise ratios, the system using the channel compensation method achieved the lowest bit error rate. This outcome was achieved by implementing hybrid modulation scheme, including Wavelength division multiplexing (WDM) and direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) techniques. It has been proved that this method can effectively reduce the channel distortion when the receiver is moving. This study develops a dependable communication system, which enhances signal recovery, reduces interference, and improves the quality and transmission efficiency of railway communication. The system has practical application value in the field of railway communication signal processing.

A hierarchical model of the information environment for railway power supply system critical objects control

It is proposed to consider the hierarchical model of the information environment as a structure according to its functions (implemented by the software part) and architecture (responsible for effective implementation of functional capabilities). It is proposed to improve the information management system of Ukrzaliznytsia’s critical power supply facilities, based on the developed hierarchical model of the information environment, which takes into account the presence of Ukrzaliznytsia’s own generation sources by integrating the appropriate control subsystem into the information system structure. The model emphasizes the integration of software and hardware components for data collection, pre-processing, and decision-making, contributing to a highly automated and intelligent control system. It proposes a multi-level structure incorporating artificial intelligence and advanced technologies to optimize electricity consumption and improve operational efficiency within the railway power supply system.

A Novel Application of Computational Contact Tools on Nonlinear Finite Element Analysis to Predict Ground-Borne Vibrations Generated by Trains in Ballasted Tracks

Predictive numerical models in the study of ground-borne vibrations generated by railway systems have traditionally relied on the subsystem partition approach (segmented). In such a method, loads are individually applied, and the cumulative effect of the rolling stock is obtained through superposition. While this method serves to mitigate computational costs, it may not fully capture the complex interactions involved in ground-borne vibrations—especially in the frequency domain. Recent advancements in computation and software have enabled the development of more sophisticated vibrational contamination prediction models that encompass the entire dynamics of the system, from the rolling stock to the terrain, allowing continuous simulations with a defined time step. Furthermore, the incorporation of computational contact mechanics tools between various elements not only ensures accuracy in the time domain but also extends the analysis into the frequency domain. In this novel approach, the segmented models are shifted to continuous simulations where the nonlinear problem of a rigid–flexible multibody system is fully considered. The model can predict the impact of a high-speed rail (HSR) vehicle passing, capturing the key intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain.

Impact of metro vibrations on people: critical aspects of designing vibration mitigation interventions

A methodology for assessing and mitigating the impact of metro infrastructure generated vibration and ground-borne noise on people is described. This methodology combines techniques for analyzing vibration measurements and predictive modeling to identify effective mitigation interventions. These interventions require working on existing railway track systems and involve interruption of service, unlike noise mitigation interventions that can be implemented without interfering with rail and road infrastructure. For this reason, it is important to identify the most effective mitigation techniques to minimize the impact on the population and simplify on-site implementation. The methodology was applied in Milan metro lines where the vibration level was estimated, and a vibration mitigation system was designed. The vibration phenomenon was quantified through accelerometric measurements taken in several buildings affected by the disturbance from vibration. The measured vibration levels were compared with reference level established by standards. The maximum difference obtained from this comparison was used as input data for the design of the mitigation intervention. The vibration mitigation interventions involve increasing the total mass and elasticity of the existing system. Their effectiveness was verified through numerical calculation using parametric software confirming the required amount of mitigation.

Failures in railway systems

Failures in railway systems

Optimizing hybrid renewable energy based automated railway level crossing in Bangladesh: Techno-economic, emission and sensitivity analysis

The railway system in Bangladesh, particularly the level crossing system, needs significant advancements, including a shift towards using renewable energy to power these crossings. As a solution, this study proposes optimal hybrid systems powered by renewable energy on an automated railway level crossing system, which is reliable, efficient, and sustainable. The main contribution of this study is to introduce an optimal hybrid renewable energy-based automated railway level crossing system in Bangladesh, focusing on technical and economic evaluation, emissions, and sensitivity assessment using HOMER Pro. The proposed system examines the optimal outcome for a 1 kW vertical-axis wind turbine and a 0.440 kW photovoltaic system at five selected locations. The results reveal satisfactory net present cost values amounting to USD 8495, USD 8505, USD 8564, USD 8262, and USD 8357 for Narayanganj, Cox’s Bazaar, Noakhali, Dinajpur, and Rajshahi respectively. Moreover, HOMER Pro indicates that the photovoltaic-wind turbine–grid-connected model offers a lower Cost of Energy which is around 0.03 USD/kWh compared to other configurations. The Internal Rate of Return for the selected locations are 20 %, 33.7 %, 31.5 %, 5.2 %, and 4.6 % for Narayanganj, Cox’s Bazaar, Noakhali, Dinajpur, and Rajshahi, respectively. The developed structure is projected to have a payback period ranging from 4.57 to 13.29 years across the five selected locations. Furthermore, the proposed systems reduce greenhouse gas emissions by up to 44.23 % compared to a grid-only system. Additionally, sensitivity analysis is performed by varying wind speed and solar irradiation to emphasize the robustness of the proposed systems.

Selected applications of satellite technologies in rail transport

Global Navigation Satellite Systems (GNSS) are increasingly being used in various modes of transport, including rail transport. When this technology is applied to railway traffic control, it is essential to ensure a high level of safety and reliability. The approval of a railway traffic control system requires a safety analysis, which includes hazard analysis and risk analysis. This also includes GNSS-based solutions in terms of their compliance with safety integrity requirements, i.e. THR (Tolerable Hazard Rate) and SIL (Safety Integrity Level) parameters, as defined in normative documents. In the case of railway traffic control systems, the level of dependability of the determined train position, referred to as position integrity, is very important in ensuring safety. Position integrity is affected by many factors, including: errors due to SIS (Signal-In-Space) propagation, multipath errors, signal interference or GNSS receiver errors. In order to improve position integrity, among other things, new data processing methods can be used to improve the accuracy and reliability of measurements. The paper presents the concept of satellite signal processing for precise determination of the position of objects in selected railway systems. The Kalman filter based model of satellite signal filtration and its selected applications, which were tested in the real condition, was presented. The application of Kalman filtration indicated in the paper is a universal method that improves the estimated measurement parameters and can be used in many applications of satellite systems for railway tasks. The applicability of satellite systems to automatic train operation, defect positioning in automatic and manual flaw detection tests, determining track spatial orientation and train integrity control have been considered. The conducted tests confirmed the correctness of the adopted concept and the model of satellite signals filtration developed for this purpose. According to the authors, the described methods can also be used in many other tasks related to rail transport.

Prospects of autonomous railway transport development

The implementation of unmanned train control systems offers a number of advantages, such as increasing the capacity of railway lines and traffi c volumes, reducing the ‘human factor’, as well as reducing operating costs. The paper considers the challenges arising from the use of automatic train control systems, and presents the prospects for the implementation of automatic technologies in railway transport for various railway systems. The social and economic aspects of changing professional activities in railway transport are described. Grades of automation applicable to surface urban railwaytransport are presented. The issues of proving the functional safety of machine vision systems as part of the train traffic control system and determining their level of safety completeness are discussed. Examples of railway transport automation in Russia and other countries are given. Basic scenarios of automatic control system operation describing normal and abnormal situations are formulated. In conclusion, the levels of technological readiness of the reviewed solutions in the fi eld of train traffic automation are defi ned. The tasks faced by railway companies in implementing these technologies are outlined, and possible ways of overcoming obstacles to the introduction of automatic systems are proposed, taking into account the current political situation.

A Network Reliability Analysis Method for Complex Real-Time Systems: Case Studies in Railway and Maritime Systems

A Network Reliability Analysis Method for Complex Real-Time Systems: Case Studies in Railway and Maritime Systems

Research on the railway multi-source homonymous geographical entity matching algorithm based on dynamic time warping

This study aims to explore an efficient technique for matching multisource homonymous geographical entities in railways to address the identification issues of homonymous geographical entities. Focusing on railway line vector spatial data, this research investigates the matching problem of multisource homonymous geographical entities. Building on statistical feature matching of attribute data, a curve similarity calculation method based on the DTW algorithm is designed to achieve better local elastic matching, overcoming the limitations of the Fréchet algorithm. The empirical study utilizes railway line layer data from two data sources within Beijing’s jurisdiction, fusing 6237 segment lines from source 2 with 105 long lines from source 1. The structural comparison between the two data sources is conducted through statistical methods, applying cosine similarity and the maximum similarity value of TF-IDF for text similarity calculation. Finally, Python is used to implement the DTW algorithm for curve similarity. The experimental results show an average DTW distance of 3.92, a standard deviation of 4.63, and a mode of 0.005. Similarity measurement results indicate that 95.53% of records are within the predetermined threshold, demonstrating the effectiveness and applicability of the method. The findings significantly enhance the accuracy of railway data matching, promoting the informatization of the railway industry, and hold substantial significance for improving railway operational efficiency and system performance.

Research on information extension of mountainous rack railway engineering based on IFC standard

In response to the practical demands for data sharing and exchange in the field of rack railway systems engineering, as well as to address the gaps in the rack railway domain within the framework of the IFC4 standard, we extend and define the rack railway domain through entity extension and custom attribute sets. By utilizing the ongoing construction of the Dujiangyan to Mount Siguniang Railway as a case study, we validate the utility of this IFC extension and modeling approach. Leveraging IfcOpenShell, we incorporate the extended data content into the generated IFC file. We present a process for extension tailored to the characteristics of rack railway engineering. This study aims to provide broader information support for the digital construction of track structures in the design phase of rack railway engineering and to facilitate more efficient data exchange and sharing.

A novel method for reducing the effect of doppler frequency shift in high-speed railway mobile communication using machine learning

Currently, high-speed railway systems are rapidly expanding worldwide, necessitating reliable and efficient mobile communication solutions. However, the Doppler frequency shift caused by the high speeds of trains presents significant challenges to communication systems, particularly those using OFDM in LTE. This paper presents a novel for Doppler frequency compensation in high-speed railway communication based on the results of estimating the train's velocity using machine learning algorithms. By leveraging advanced algorithm such as neural networks, our method dynamically predicts and compensates for Doppler shifts in real-time. In this proposed novel, the Doppler frequency value is calculated based on the actual train’s velocity and the scenario of a high-speed railway, then the Doppler frequency is used to compensate the carrier frequency offset (CFO) directly at the Access Point (AP) device on the train. We conduct simulations to evaluate the effectiveness of our proposed solution in a high-speed railway scenario. The results demonstrate a marked improvement in communication reliability and data integrity, highlighting the potential of machine learning to enhance the performance of mobile communication systems in high-speed railways. The results of the proposed model are evaluated based on the system’s bit error rate BER after the CFO compensation decreases and the ratio of average energy per bit (Eb) to noise power density (N0) (Eb/N0) increases. This shows that the proposed solution works effectively and reduces the system’s bit errors while improving the communication performance. This study opens new avenues for integrating intelligent systems in transportation networks, ensuring seamless connectivity, and improving passenger experience

Algorithmic Decomposition of Railway Objects for Distributed Interlocking System

Railway interlocking systems can be implemented as distributed systems, where each part of a station is handled by a separate logical unit. The logical units of such systems form a network and communicate by interchanging messages. Such distributed architectures are well known in large industrial control systems. There are several design practices and also algorithmic task partitioning methods that are applicable in distributed control systems. Some of such methods can also be adapted in designing of railway interlocking systems as well. In the case of such systems, the communication time between components must be kept low. Namely each separate controller in a given route must be able to exchange their internal state within a limited time in order to permit the train movement authorization. This limitation could cause high traffic load, if every logical unit would be interconnected with each other. Therefore, the main goal of the minimization is to reduce the number of connections between logical units. This can achieved by distributing and assigning the topological railway objects to certain logical units.

The evaluation of wear processes of the rolling-sliding contact by means of flake wear debris in dry and wet contact

One of the tasks of this paper is to explain the cause-and-effect relationship of the influence of operating parameters on the wear of the wheel-rail system where fatigue processes are initiated. In this way, learning about and defining the nature of the phenomenon, makes it possible to determine the reliability of component operation. The aim of this study was to determine the influence of operational parameters on tribological properties of the rolling-rail contact representing the wheel-rail association in real operating conditions. Determining the form of wear on the basis of laboratory tests carried out on an Amsler-type wear testing machine in the wheel-roller system makes it possible to determine the nature of changes occurring as a result of cyclic interaction of normal and tangential forces on the surface of the tested material, without the need for long-term and costly observation of the tested object in normal operation. Quantitative metallographic analysis of the morphology of wear debris was used to determine the intensity of surface wear. Determination of the influence of operational parameters on the stereological characteristics of wear debris makes it possible to predict the regenerative grinding of rails in service in the track and allows practical application by the sections of operation and diagnosis of the railway system.