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In recent years, longer and heavier trains have become more common, primarily driven by efficiency and cost‐saving measures in the railroad industry. Regulation of train length is currently under consideration in the United States at both the federal and state levels, because of concerns that longer trains may have a higher risk of derailment, but the relationship between train length and risk of derailment is not yet well understood. In this study, we use data on freight train accidents during the 2013–2022 period from the Federal Railroad Administration (FRA) Rail Equipment Accident and Highway‐Rail Grade Crossing Accident databases to estimate the relationship between freight train length and the risk of derailment. We determine that longer trains do have a greater risk of derailment. Based on our analysis, running 100‐car trains is associated with 1.11 (95% confidence interval: 1.10–1.12) times the derailment odds of running 50‐car trains (or a 11% increase), even accounting for the fact that only half as many 100‐car trains would need to run. For 200‐car trains, the odds increase by 24% (odds ratio 1.24, 95% confidence interval: 1.20–1.28), again accounting for the need for fewer trains. Understanding derailment risk is an important component for evaluating the overall safety of the rail system and for the future development and regulation of freight rail transportation. Given the limitations of the current data on freight train length, this study provides an important step toward such an understanding. [ABSTRACT FROM AUTHOR]

Major railway projects are large-scale, complex systems involving multiple stakeholders, and the risks during the construction process can be multifaceted and constantly evolving. To enhance the risk prevention and control capabilities in such projects, according to resilience theory, the study proposed a resilience management model based on risk prevention and control and outlined a framework for resilience construction management mode in major railway resilience construction projects. Using stakeholder theory, an integrated virtual organizational structure model for major railway construction was introduced. The resilience construction management mode combined organizational management and intelligent project management, embedding risk prevention and control into the organizational management system. This approach enhanced the resilience of organizational structure, strengthened its capacity to respond to risks and challenges, and leveraged intelligent technologies to boost collaborative capabilities. Additionally, the operational mechanism of resilience management was analyzed, which was governed by contractual, administrative, and trust-based relationships. The research results provide theoretical insights and decision-making strategies for risk prevention and control in major railway projects. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the 1850s, Portugal initiated an ambitious public works program spearheaded by railroads. In this article, I analyze how policymakers (congressmen, government officials, engineers, and military officers) debated and managed the construction and operation of the Portuguese railroad network using the theoretical framework of critical infrastructure. I show that railroads were deemed critical to modernize the country, draw it closer to the European core nations and further from the periphery, and to attract traffic to the Portuguese harbors. The absence of railroads was considered a vulnerability that could jeopardize Portugal as a nation and it fostered a sense of urgency that motivated policymakers to act, to a large extent, hastily. The construction of the network brought about other vulnerabilities that, for different motives, could threaten the future of the country. In a parallel way, the implementation of the system was marked by vulnerabilities that originated within or surrounding it, which limited its technical potential. Balancing between a literature review and the use of primary sources (parliamentary debates, technical reports, the press, and photography), I argue that the criticality associated with railroads, as a sociotechnical construction, was central to motivate their construction, but different vulnerabilities, inherent or external to the system, limited their influence and the advantages touted by its promoters. [ABSTRACT FROM AUTHOR]

Ballast serves a vital structural function in supporting railroad tracks under continuous loading. The degradation of ballast can result in issues such as inadequate drainage, lateral instability, excessive settlement, and potential service disruptions, necessitating efficient evaluation methods to ensure safe and reliable railroad operations. The incorporation of computer vision techniques into ballast inspection processes has proven effective in enhancing accuracy and robustness. Given the data-driven nature of deep learning approaches, the efficacy of these models is intrinsically linked to the quality of the training datasets, thereby emphasizing the need for a comprehensive and meticulously annotated ballast aggregate dataset. This paper presents the development of a multi-dimensional ballast aggregate dataset, constructed using empirical data collected from field and laboratory environments, supplemented with synthetic data generated by a proprietary ballast particle generator. The dataset comprises both two-dimensional (2D) data, consisting of ballast images annotated with 2D masks for particle localization, and three-dimensional (3D) data, including heightmaps, point clouds, and 3D annotations for particle localization. The data collection process encompassed various environmental lighting conditions and degradation states, ensuring extensive coverage and diversity within the training dataset. A previously developed 2D ballast particle segmentation model was trained on this augmented dataset, demonstrating high accuracy in field ballast inspections. This comprehensive database will be utilized in subsequent research to advance 3D ballast particle segmentation and shape completion, thereby facilitating enhanced inspection protocols and the development of effective ballast maintenance methodologies. [ABSTRACT FROM AUTHOR]

Using dynamic game theory, this paper analyzes the interest relationship between government supervision departments, railway passenger transport enterprises and integrated service agents in the service management system of railway passenger transport enterprises in China. A tripartite dynamic game model of government supervision department, railway passenger transport enterprise and integrated service agent is established. Inverse induction algorithm is used to solve the game model, and the expected return equilibrium solution of government supervision department, railway passenger transport enterprise and integrated service agent is analyzed. The results show that the cost of railway passenger transport service management and the intensity of management are important factors affecting the implementation of service requirements by railway passenger transport enterprises and integrated service agents. Therefore, the government supervision department should reduce the management cost, design a reasonable reward and punishment mechanism, and improve the enthusiasm of railway passenger transport enterprises and integrated service agents to strengthen service management and improve service quality. Railway passenger transport enterprises and integrated service agents should actively strengthen service management, improve service quality, reduce management pressure and cost at the next level, and promote the healthy development of railway passenger transport market through a virtuous cycle between the three. [ABSTRACT FROM AUTHOR]

Global demand for fossil fuels is highly increasing, necessitating energy efficiency to be enhanced in transitioning to low-carbon energy systems. Electric railways are highly efficient in reducing the transportation demand for fossil fuels as they are lightweight and their energy demand can be fed by renewable energy resources. Further, the regenerative braking energy of decelerating trains can be fed to accelerating trains and stored in onboard energy storage systems (ESSs) and stationary ESSs. It is fundamental to model electric railways accurately before investigating approaches to enhancing their energy efficiency. However, electric railways are challenging to model as they are nonlinear, resulting from the rectifier substations, overvoltage protection circuits, and the unpredictability and uncertainty of the load according to the train position. There have been few studies that have examined the ESS location's impact on improving the energy efficiency of electric railways while using specialised simulation tools in electric railways. However, no single study exists that has studied the location impact of stationary ESSs on the energy efficiency of electric railways while the trains are supported by onboard ESSs. Given these goals and challenges, the main objective of this work is to develop a model using commercial software used by industry practitioners. Further, the energy saving is aimed to be maximised using stationary ESSs installed in optimal locations while trains are supported by onboard ESSs. The model includes trains, onboard ESSs, rail tracks, passenger stations, stationary ESSs, and traction power systems involving power lines, connectors, switches, sectioning, and isolators. In this article, a test scenario is presented comprising two trains running on a 20 km with three passenger stations and two substations. The trains and track are modelled in OpenTrack simulation software (Version 1.9) while the power system is modelled in OpenPowerNet simulation software (Version 1.11). The two simulation tools are used in the railway industry and can produce realistic results by taking into account the entire electrical network structure. A stationary ESS is added on the wayside and moved in steps of 1 km to obtain the optimal location before investigating the impact of stationary ESSs on the performance and energy management of onboard ESSs. It is found that the energy saving when installing a stationary ESS at the optimal location is 56.05%, the peak-power reduction of Substation 1 is 4.37%, and the peak-power reduction of Substation 2 is 18.67%. [ABSTRACT FROM AUTHOR]

In the railway system environment, the interconnection of a vast array of intelligent sensing devices has brought about revolutionary changes in the management and monitoring of railway transportation. However, this also poses challenges to the communication service quality within the railway Internet of Things (IoT). Through collective intelligence and collaboration, the nodes within the railway IoT can not only share data and information but also work synergistically to enhance the overall intelligence level and improve decision-making quality of the network. Therefore, this paper proposes a reconnection mechanism based on the computation of node game-theoretic benefits and optimizes this process with the concept of swarm intelligence collaboration. Initially, the game-theoretic benefit values of the nodes in the railway IoT network are calculated. Subsequently, based on the weight priority of the edges, the two edges with the larger weights are selected, and connections are established between nodes with similar game-theoretic benefit values to enhance the network's robustness. This approach enables rapid networking and efficient communication transmission within the railway IoT, providing robust assurance for the safe and stable operation of the railway. [ABSTRACT FROM AUTHOR]

Regular monitoring and inspection of military railroad tracks are necessary to ensure the safe transportation of military freight. Manual railroad inspection has drawbacks and limitations that can impact accuracy and efficiency. This study introduces a novel tool designed to automate Ground Penetrating Radar (GPR) imaging interpretation for railroad ballast condition assessment, aiming to reduce human intervention in inspections. The tool uses advanced signal processing techniques, such as the Short-Time Fourier Transform (STFT) and Wavelet Transform (WT), to quantify ballast fouling levels accurately, enhancing maintenance and safety protocols for railroad tracks. Validation through comprehensive testing, including two case studies, demonstrates the tool's superior efficacy over traditional manual inspection methods. This research represents a pivotal step towards more efficient and reliable infrastructure management, ensuring critical railroad systems' safety and operational integrity. [ABSTRACT FROM AUTHOR]

This study aims to comprehensively assess the lubrication effect of leaves on wheel–rail contact dynamics using the Virginia Tech-Federal Railroad Administration (VT-FRA) Roller Rig, which closely simulates field conditions with precision and repeatability. Railway operators grapple with the seasonally recurring challenge of leaf contamination, which can cause partial loss of braking and lead to undesired events such as station overruns. Better understanding the adhesion-reducing impact of leaf contamination significantly improves railway engineering practices to counter their effects on train braking and traction. This experimental study evaluates the reduction in traction and braking forces (collectively called "adhesion") as a function of leaf volume, using two leaf species that commonly grow along U.S. railroad tracks. The test methods rely on the chosen leaves' transpiration characteristics while ensuring the result's reproducibility. Leaves were symmetrically positioned on the wheel surface, centered around the mid-rib area within the wear band, and taped on the edges far from the wear band. The critical test parameters (i.e., wheel load, wheel velocity, and percentage creepage) are kept constant among the tests. At the same time, leaf volume is reduced from a maximum amount that covers the entire wheel surface (100% coverage) to no leaves (0%). The latter is used as the baseline. The percentage creepage is kept constant at an exaggerated amount of 2% to accelerate the test time. The results indicate a nonlinear relationship between leaf volume and the loss of braking. Even a small amount of leaf contamination causes a significant reduction in adhesion by as much as 50% compared with no contamination (i.e., baseline). Increasing leaf volume results in contact saturation, beyond which adhesion is not reduced. The minimum adhesion observed in this study is 20% of the maximum adhesion that occurs when no leaf contamination is present. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economic Research & Business Administration is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Workforce shortages during the COVID-19 pandemic and the recent threat of railroad strike in the United States have generated greater public awareness of how freight flow disruptions can harm society. Unlike highways, trains often do not have the ability to take alternative routes that directly connect major metropolitan areas; hence railroad networks are vulnerable to disruptions like accidents. This study developed a data mining workflow to rank commodity movements that are at the highest risk of disruption from railroad accidents and other types of regional disasters that can affect railroad operations. A key finding is that five U.S. metropolitan areas are at least five times more likely than others to experience a railroad accident. Those five areas account for more than 40% of the monetary value in alcoholic beverages, raw meats, gasoline, plastic-based products, and rubber-based products moved by rail. Hence, any disruption in those five areas can lead to widespread shortages of those commodities. The implication is that decision makers should focus risk mitigation and resiliency strategies in those five metropolitan areas and on the top commodity categories at risk. [ABSTRACT FROM AUTHOR]

The cloudification and virtualisation of railway functions have the potential to improve railway operation efficiency, reliability, safety, and security, as well as to enhance passenger experience by offering innovative services. This paper considers issues related to the management and orchestration of railway clouds that host cloudified railway functions. A microservices-based approach to the design of railway cloud management and orchestration functionality is proposed. The basic railway cloud concepts were defined, and functionality related to the basic orchestration of the railway cloud and deployments is analysed in order to derive the requirements of platform resources and workload management. This functionality is further designed in the form of microservices, meaning that they could possibly be used in orchestration applications to enable improvements in scalability, fault isolation, and data security. The design of microservices follows the principles of the Representational State of Transfer (REST) application programming interface (API) as a set of interlinked resources. Resources related to railway cloud orchestration are identified with their associated data, relationships to other resources, and applicable methods. The resources' methods are used in railway applications to implement the required orchestration functionality and to maintain the state of railway cloud orchestration processes. To verify the synthesised microservices, the common orchestration application logic and microservices' logic were modelled, and it was proved that the orchestration processes, which run concurrently, expose equivalent behaviour. The proposed approach was validated using a simulation, aiming to evaluate injected latency as a key performance indicator for the reliability and safety of railway operations. Additionally, some safety and security issues related to railway cloud management and orchestration are considered. [ABSTRACT FROM AUTHOR]

The prolonged Covid-19 pandemic and resultant sporadic lockdowns have led to a decline in demand for travel, causing the number of railway passengers to decline. In Japan, the railways are run by private operators, whose businesses and earnings have been severely affected. In this study, based on Japanese listed railway companies' investor relations information, we analyze how the Covid-19 pandemic influenced a decline in their revenues and changes in their profit structures. In addition, we conducted a text analysis of the differences in management strategies between loss-making and profitable companies and explored the management strategies that characterize profitable companies. The results suggest that to achieve a profit structure that remains sustainable post-pandemic, private railway companies need to strengthen the non-transportation business segment because it generates enough revenues to compensate for the loss-making segments. Further, they should review their management strategy from the perspective of the corporate brand, organization, finance, and business segments beyond existing ideas. The theoretical contribution of this study proposes that managers of railway operators or public sector policymakers can assess the impact of a severe impact on the demand for railway services, such as the Covid-19 pandemic. And it enables quantitative analysis, such as examining business portfolios to avoid risk and estimating future railway passenger forecasts. The results of this study provide suggestions for management strategies for corporate groups centered on railways to sustain and develop stable railway operations in the event of a significant decline in demand for railways such as a pandemic, disaster, dispute, and so on. And it can be used for subsidies and other support from the public sector to railway operators as well as private railway companies, and for policy making. • Conduct quantitative assessment of the Japanese railway company's business segments. • Examine management policies through text analysis after the Covid-19 pandemic. • Indicate transportation-related business segment is affected by the Covid-19 pandemic. • Profitable companies generate revenue in their core business by management strategy. [ABSTRACT FROM AUTHOR]

The object of research is railroad passenger transportation. The subject of research is a change management system. The problem to be solved is to improve the efficiency of railroad transport enterprises in the field of passenger transportation by introducing a change management system. In the study, the concept of the formation of a change management system in the field of passenger transportation of railroad transport in Ukraine under wartime conditions was devised. Since the conditions of war refer to a variety of emergencies, the concept of “emergency situation”, its types, characteristics, and signs that describe its existence are considered. The conditions of emergencies are defined. The properties of total and hybrid war affect the fundamental features of the state management of railroad passenger transport in Ukraine, the work of state departments and railroad passenger transport management enterprises. Taking into account the peculiarities of each type of war and the principles of the state, a system of interconnection of the features and principles of the state management of railroad passenger transportation with possible aggressive changes under wartime conditions was built. Such a system is the core of the devised concept of formation and modeling a change management system in the field of railroad passenger transportation in Ukraine under war conditions. Within the framework of the concept, a strategy is formed – a set of actions during an emergency of a military nature. Based on this concept, in the future, it is possible to construct stages of research, the existence of which could make it possible to build a model of the concept, namely the processes of forming a system of changes. [ABSTRACT FROM AUTHOR]

The construction of major railway projects poses significant risks, which present considerable challenges to construction management. To accurately assess the level of construction management for these projects, this study incorporated resilience theory into the field. The grounded theory method was utilized to establish a resilience evaluation indicator system for managing a major railway project construction. Additionally, a resilience evaluation model based on the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation method was proposed. This model was applied to evaluate the construction management resilience of a major railway project located in the mountainous region of southwest China. The results indicated that the project exhibits a very high overall level of construction management resilience. Specifically, it demonstrates high levels of ability to monitor and warn, an ability to resist absorption, and an ability to respond to emergencies. Additionally, it showcases high levels of ability to recover and rebuild, and an ability to learn to adapt. The evaluation results were consistent with the actual situation and verified the correctness and reliability of the method. Based on the aforementioned research findings, this paper puts forward recommendations on material redundancy and resource security from a resource perspective, and suggestions on organizational optimization and personnel capacity improvement from a subject perspective, thus indicating directions for enhancing the management level of major engineering railway constructions. [ABSTRACT FROM AUTHOR]

The safety and reliability of undivided two-way highway–rail grade crossings (HRGCs) are of paramount importance in transportation systems. Utilizing crash data from the Federal Railroad Administration between 2020 and 2021, this study aims to predict crash injury severity outcomes and investigate various factors influencing injury severities. The χ2 test was first used to select variables that were significantly associated with injury outcomes. By employing the eXtreme Gradient Boosting (XGBoost) model and interpretable SHapley Additive exPlanations (SHAP), a cross-category safety assessment that offers an evidence-based hierarchy and statistical inference of risk factors associated with crashes, crossings, vehicles, drivers, and environment was provided for killed, injured, and uninjured outcomes. Some significant predictors overlapped between the killed and injured models, such as old driver, driver was in vehicle, main track, went around the gate, adverse crossing surface, and truck, while the other different significant factors revealed that the model could distinguish between different severity levels. Additionally, the results suggested that the model has varying performances in predicting different injury severities, with the killed model having the highest accuracy of 93.36%. The SHAP dependency plots for the top three features also ensure reliable predictions and inform potential interventions aimed at strengthening traffic safety and risk management practices, such as enhanced warning systems and targeted educational campaigns for older drivers. [ABSTRACT FROM AUTHOR]

Huge regenerative braking (RB) energy is generated in the AC traction power supply system (TPSS) which is related to safe operation and comprehensive energy utilisation. For the RB energy utilisation, the authors propose a railway regenerative braking power conditioner (RBPC) with no energy storage system (ESS) integrated which is located at the end of the power sections between adjacent traction substations (TSSs). First, the RB characteristics are studied based on a large amount of measured data, and the load power states are classified according to the load powers of adjacent power sections. Then, the RB energy utilisation scheme, transferring the RB power to the adjacent power section where traction power exists, has been studied. Moreover, a dual closed‐loop control strategy for a back‐to‐back converter is adopted to achieve RB energy utilisation. Finally, a case study and an engineering application are carried out. The results have verified the feasibility of this method, which can illustrate that more than half of the RB energy can be mutually utilised in adjacent power sections. [ABSTRACT FROM AUTHOR]

RFID (radio frequency identification) is a progressively adopted technology in today's automated world. Wireless technologies have enabled contactless payments, tracking, identifying, and many more features in a system that can be introduced to build a smart environment. This work overviews the usage of the IoT (Internet of Things) platform for tracking passengers and enabling online payments through wireless sensors and RFID technology in Chennai Suburban Railways. The tracking system consists of an RFID reader that can locate and track passive as well as mobile objects attached with passive RFID tags. The proposed system incorporates the installation of RFID readers at every entrance and exit of the railway station, and every passenger carries their own RFID tags. This not only enables online payments for passengers but also helps the government in tracking the crowd for demand monitoring. The new methodology creates a digital workspace and enforces lawful safety regulations both for the administration and the consumers. A prototype of the proposed system is implemented in real-time to understand the workings of the system. Data collection is done through RFID tags that act as transit cards and an analysis for consumer demand is done using the DBSCAN (Density-Based Spatial Clustering of Application with Noise) algorithm with a Randomized KD-tree for the analysis of spatial and temporal patterns. A new algorithm, the iDBSCAN (improved Density-Based Spatial Clustering of Application with Noise) algorithm is proposed for faster performance on the datasets. [ABSTRACT FROM AUTHOR]

Sichuan-Tibet Railway spans several watersheds such as Jinsha River and Yalong River, and Potential landslides are frequent along the route, which poses serious hazards to the normal construction and operation of the railroad. The traditional time-series InSAR technology is limited by the number of images and other restrictions, and has a long solution time, making it difficult to obtain information on short-term occurrence of deformation and unable to perform wide-area potential landslides monitor quickly. In this paper, taking a geological hazard-prone area in the Jinsha River basin (or a section of the Sichuan-Tibet line) as an example, based on the Sentinel-1 satellite SAR data provided by the Copernicus program of ESA, the model corrects the interferometric superposition deformation results obtained from a small number of SAR images (less than 7), decodes the corrected rate results, and identifies a total of 13 areas where deformation obviously occurs A total of 13 typical areas with significant deformation were identified. The identified typical areas were time-series solved and their deformation was traced. The method provides a new idea for identification and monitor of Potential landslides in a wide area and further promotes the development of disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Rail surface damage occurs due to repeated overstressing of the surface by wheel-rail contact cycles, which is also known as rolling contact fatigue, and causes regular costly maintenance expenses to railways. The preventive strategies to reduce rail damage can be conservative if it is not based on measured data. A validated digital model of the physical system can provide data for maintenance decision. Interaction between a physical system and a digital model has evolved at the beginning of this century into a new process commonly referred to by the term 'Digital Twin'. There is a lack of a Digital Twin framework in decision-making on railway maintenance. The term Digital Twin is often confused with advanced simulation methods where the communication of data is only one way, i.e. sensor or design data of the physical system input to a model. In this paper, a Digital Twin has been developed to predict rolling contact fatigue rail surface damage, corresponding to traffic passing along a railway network. Differences between the Digital Twin and advanced simulation techniques have been presented. Finally, a predictive assessment tool has been proposed to provide prediction from the Digital Twin to the physical twin, and results are discussed. Abbreviations: AS: Advanced Simulations; DS: Digital Shadow; DT: Digital Twin; HPC: High Performance Computing; LTS: Longitudinal Train Simulation; MBS: Multibody Simulation; MGT: Million Gross Tonnes; NASA: National Aeronautics and Space Administration; RCF: Rolling Contact Fatigue [ABSTRACT FROM AUTHOR]

The information that automated train control (ATO) systems use to improve safety and reduce power usage is limited by on-board and wayside monitoring applications and computing power. This paper presents an augmented digital twin for railway applications that enables real-time consideration of derailment risk in train operations. The augmented digital twin implements a surrogate model with the results of a massive multibody dynamics numerical program and machine learning models to predict the instantaneous wagon derailment risk. A case study for a heavy haul iron ore wagon with three-piece bogies was conducted to test the augmented digital twin. A multibody simulation numerical program comprising 2100 simulation cases was completed. The surrogate model was developed using linear, polynomial, decision tree and ensemble forest regression models on the results of the numerical program. A longitudinal train simulator was used to calculate the speed and lateral coupler force throughout a train trip. The surrogate model effectively predicted the derailment index for empty and loaded conditions accounting for lateral coupler forces, vehicle speeds and curve radius. The proposed augmented digital twin can be further developed to accomplish other train operational benefits such as the reduction of rail damage. [ABSTRACT FROM AUTHOR]

Safety management is a key issue in the railroad industry that needs to be continuously focused on. And it is essential to study causes of accidents for preventing accidents. However, there is a limited academic discussion on the systematic study of organizations and accidents, as well as their safety-related interactions and accidents, as opposed to human-caused disasters. Thus, the model of China's railway safety supervision and management system by sorting out the existing organizations involved in management in China is established in this paper. Firstly, social forces and auxiliary enterprises are specifically added to the model. And then, the relationship between organizations and accidents, as well as the relationship between safety interactions among organizations and accidents are explored by analyzing 224 accident reports, which led to 4 principles for accident prevention. Finally, based on these principles, measures to secure organizational nodes, as well as measures to promote safe interactions among organizations are proposed. The results showed that: (1) China Railway node is not only the most critical node in the safety supervision and management system but also the most vulnerable to the influence of other nodes. (2) The accident occurred due to the simultaneous occurrence of an accident at the China Railway node and the social force node. (3) When there are often safety risks in auxiliary enterprises and social forces simultaneously, the government's management is likely to be defective. The findings in this study can provide helpful references not only for improvement of safety management system structure and supervision and management mechanism but also for the formulation of safety supervision and management policies in China and other countries. [ABSTRACT FROM AUTHOR]

Because imbalanced power will cause the loss of the propulsion motor of the railway vehicle, and the increase in temperature will shorten the service life of the electric vehicle. Not only this but also increase the cost of electricity and maintenance. In the past, the industry only focused on methods to improve power quality such as load capacity, relay setting, and harmonic resolution. Now, the consider of three-phase unbalance rate (TPUR) must be applied. I propose special transformers wiring (STW) to improve the three unbalance rates and provide different transformer wiring methods. According to the IEEE Committee, in the future, power companies will need to install balanced relay stations to improve three-phase unbalance rate. The internal regulations of Taipower must be less than 4.5% (voltage unbalance rate (NPSUR) of 2.5% and motor temperature rise of 12.5%). The derivation of the transformer "three-phase unbalance rate" model is the focus of the railway system. This research is based on the model derivation of different wiring methods to improve the problem caused by the three-phase imbalance and improve the using life of the train. They pointed out that Scott, Le-Blanc, and Modified-Woodbridge, the three wiring methods can be applied to future railway system and reduce the three-phase unbalance rate. They are in line with the IEEE standard ( % P U V ) of less than 2%. [ABSTRACT FROM AUTHOR]

The railway industry—traditionally a conservative industry with low adaption speed for innovation—is currently entering its digitization phase. The sector faces a challenge in integrating new technologies and approaches into the employed—often safety-critical—systems. Keeping the systems secure while conforming to the demanding safety norms creates previously unknown problems. In the last decades, the number of attacks on the railway system has increased. Furthermore, with standardized digital technologies, the attack surface will keep growing. Therefore, in this work, we look into the foreseeable future of the railway system and present 21 likely use cases. We analyze these use cases regarding possible threats, rate the severity of these threats, and deduce and rate necessary countermeasures. To this end, we model these use cases and the corresponding threats and countermeasures using Attack Graphs. We use a graphical solution for the risk and security analysis due to advantages over other methods, i.e., table-based solutions, like simplified presentation and an easier understanding of relationships, dependencies, and interactions between various elements. From these Attack Graphs, we extracted 14 commonly recurring attack strategies. After analyzing 49 countermeasures regarding their current maturity and further research and standardization demands, we identified 21 in need of further investigation. This implies that 21 necessary countermeasures to secure these future use cases require further research to apply to railway systems or require standardization. These results will help researchers focus on the necessary research and standardization and railway operators to ensure the security of their systems. [ABSTRACT FROM AUTHOR]

This paper discusses the practice and application of IRIS configuration management in railway signal engineering projects in view of the practice in railway projects. The technology management means related to IRIS configuration management are used to ensure product traceability, safety and reliability in the project life cycle, thus playing a very important supporting role. [ABSTRACT FROM AUTHOR]

Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations. In this paper, we propose a rescheduling model that incorporates constraints and objectives generated through human-computer interaction. This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling. The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework. We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions. By summarizing rescheduling rules, we devise a rule-based conflict detection-resolution heuristic algorithm to effectively solve the formulated model. A series of numerical experiments are presented, demonstrating strong performance across the entire system. Furthermore, the flexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of human-computer interactions in the previous step. This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions. It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies. [ABSTRACT FROM AUTHOR]

This study addressed the issues related to the collection and management of basic data for railway green performance. A railway green performance basic database has been constructed based on metadata and data ex-change schemas. A data classification system has been established from the perspectives of businesses, processes, and entities. A BIM (Building Information Modelling) model data extraction scheme is proposed based on field similarity matching and a document content extraction scheme is proposed based on image recognition. A railway green performance basic data collection system has been developed, achieving efficient collection and integrated management of railway green performance basic data. This system can provide data support for applications such as railway carbon emissions accounting, green cost-benefit analysis, and evaluation of green design solutions. [ABSTRACT FROM AUTHOR]