Rail Transport Research Articles

A novel six-dimensional digital twin model for data management and its application in roll forming

Roll forming is a cost-effective, efficient, and flexible plastic processing technique that involves the gradual transverse bending of metal strips using sequentially arranged forming dies. It is an important technological approach in response to lightweight, energy efficiency, and safety in various sectors, including new energy vehicles, aerospace, and rail transportation. However, the complexity of the process, diverse data types, and the effects of coupling and nonlinearity have led to challenges in process stability and quality control. The unclear impact mechanism of heterogeneous time-series data from multiple sources on product quality significantly hinders the development and widespread adoption of roll forming in industries. To facilitate the study of its mechanisms and optimize the control of forming quality, this paper introduces a digital twin (DT) model tailored for the roll forming field. It also presents a product-oriented feature data management framework based on the DT model. This framework facilitates feature-based data categorization across the complete lifecycle, enabling advanced data analysis in the roll forming domain. The feasibility and advantages of the proposed model and framework are validated through application to produce hat-shaped components. It is hoped that the work can provide valuable insights to the digitalization and intelligent transformation of roll forming field.

Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation.

To date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging infrastructure, and adverse environmental conditions on the one hand, and the scale, complexity, and critical safety implications of railway systems on the other. Our study is underpinned by the three objectives. Specifically, we aim to identify time series anomaly detection methods applied to railway sensor device data, recognize the advantages and disadvantages of these methods, and evaluate their effectiveness. To address the research objectives, the first part of the study involved a systematic literature review and a series of controlled experiments. In the case of the former, we adopted well-established guidelines to structure and visualize the review. In the second part, we investigated the effectiveness of selected machine learning methods. To evaluate the predictive performance of each method, a five-fold cross-validation approach was applied to ensure the highest accuracy and generality. Based on the calculated accuracy, the results show that the top three methods are CatBoost (96%), Random Forest (91%), and XGBoost (90%), whereas the lowest accuracy is observed for One-Class Support Vector Machines (48%), Local Outlier Factor (53%), and Isolation Forest (55%). As the industry moves toward a zero-defect paradigm on a global scale, ongoing research efforts are focused on improving existing methods and developing new ones that contribute to the safety and quality of rail transportation. In this sense, there are at least four avenues for future research worth considering: testing richer data sets, hyperparameter optimization, and implementing other methods not included in the current study.

Forecasting train arrival delays on the Ankara – Eskişehir high-speed line in Turkey

Railway operations may experience delays due to technical issues or weather conditions. Accurate prediction of such delays can enhance the quality of rail transport services and the effectiveness of railway operations. The study has developed the arrival delay prediction model using random forest regression based on the train operation data from the Ankara - Eskişehir high-speed train line in Turkey. The model can simultaneously predict arrival delays at all downstream stations on this line and continuously update these predictions as new information about train movements becomes available. The accuracy rates of the model vary from 76% to 99% under a 1-min prediction error. The results show that incorporating variables related to weather conditions and technical problems related to train control systems into the model improves prediction performance. The contribution of these variables to the model performance increases as the prediction horizon widens. The model results suggest that the model predictions may assist network managers in making better decisions about train operations. In order to evaluate the model's performance from the passengers' point of view, the study has proposed two methods: the proportion of late predictions and the stability of forecasts. The findings indicate that most trains (between 96.7% and 99%) have stable arrival delay predictions at target stations. The proportion of 2-min (or greater) late predictions, which means that the predicted delay exceeds the actual delay by 2 min or more, fluctuates from 14% to 0.5%, depending on the prediction horizon. Although the ratio for the short horizons (one station ahead) becomes relatively low, it is necessary to be cautious when using the model predictions to inform passengers because a prediction of more than 1 min late for short horizons might have negative consequences (e.g., misleading passengers to leave stations).

Increasing supply chain resiliency through equilibrium pricing and stipulating transportation quota regulation

Supply chain disruption can occur for a variety of reasons, including natural disasters or market dynamics for which resilient strategies should be designed. If the disruption is profound and has dire consequences for the economy, it calls for the regulator’s intervention to minimize the impact for the betterment of the society. This paper investigates the minimum quota regulation on transport amounts of a shipping company with limited capacity that transports a group of products with heterogeneous transportation and production costs and prices. An interesting example can be found in the North American rail transportation market, where rail capacity is used for a variety of products and commodities, such as oil and grains. Similarly, in Europe, the supply chain for grain produced in Ukraine is disrupted by the Ukraine war and the blockade of the maritime transport routes. This siege puts pressure on the rail transport capacity of Ukraine and its neighboring countries to the west, which needs to be shared to ship a variety of products, including grains, military, and humanitarian supplies. Such situations require the proper execution of government intervention for effective management of limited transport capacity to avoid rippling effects throughout the economy. We propose mathematical models and solutions for market players and the government in a Canadian case study. Subsequently, the conditions that justify government intervention are identified, and an algorithm is presented to obtain the optimum minimum quotas.

An instance-based transfer learning model with attention mechanism for freight train travel time prediction in the China–Europe railway express

Since the inception of the China–Europe Railway Express (CRE), rail transportation has emerged as a predominant means of transporting goods across international borders. The quality and reliability of railway transport services are constrained by the precision of train travel times. However, the real-time data available for the CRE trains is rather limited due to the volume and duration of operations, which increases the difficulty of forecasting CRE train travel times. In order to enhance the accuracy of predictions, a novel two-stage transfer learning model with the Long Short-Term Memory attention (T.R2_LSTM_A) is introduced in this study. By incorporating attention mechanisms, the Long Short-Term Memory networks (LSTM) module, the two-stage TrAdaBoost.R2 algorithm, and transfer learning (TL), the model captures the inherent characteristics of time series data and attains a high level of accuracy in predictions. This approach effectively mitigates the limitations of current transfer learning methods, which are primarily caused by insufficient sample data. In the model, an instance-based TL method is utilized to address the shortcomings of insufficient data, and an attention-based LSTM is selected as a base learner to overcome the thorny issues of gradient disappearance and explosion. Additionally, LSTM Attention (LSTM_A), a novel attention mechanism, is introduced to improve the ability of the proposed model to capture complicated characteristics. The T.R2_LSTM_A model is systemically evaluated and shown to be superior to Random Forest (RF), Support Vector Regression (SVR), LSTM, convolution-based LSTM (CLSTM), AdaBoost_LSTM, LSTM with attention mechanism (LSTM_Attention), and TrAdaBoost.R2_RF (T.R2_RF) for predicting train travel time, using a real-life case study of CRE. The MSE, RMSE, MAPE, and MAE values for the T.R2_LSTM_A model are equal to 5.572, 2.361, 2.578, and 1.767, respectively. These values surpass those of other widely used prediction methods, indicating that the T.R2_LSTM_A model is well-suited for predicting train travel times in the CRE.

Competition in the ‘body without organs’: an assemblage perspective on the UK’s fast train (HS2) cancellation

ABSTRACT In this contribution, an investigation is made into the abandonment of a very large infrastructural investment by the UK government. It was the HS2 (High Speed 2) train ‘assemblage’ for the 345 miles from Leeds in the North to London. It occurred in the belief that such expenditure would ‘level-up’ the worsening regional economic disparities between the two regions and render the North (dubbed the ‘Northern Powerhouse’ by successive governments) ‘competitive’. In reality, there was no evidence in support of the idea that a faster rail service would have this effect. Critics realized London’s advantage could not be competed against. This was because its advantage as an unregulated ‘tax haven’ had been entrenched since even before William the Conqueror’s invasion in 1066. Our take on this débâcle is that it was caused by hubris on the part of successive governments, culminating in the growth of distrust between politicians and the people, including ‘experts’ who were singled out for special ministerial disdain. The analysis explores ‘assemblage’ theory and its psychological origins, in which desire has come to substitute for thought in the UK political arena. Accordingly, desire has been swallowed up by ‘competitiveness’, meaning mistakes were made due to hubris, narcissism and criminality because of the politics of ‘we know better’ on the part of the political élite. The cost of these mistakes was upwards of £36 billion for the biggest UK rail infrastructure project in a hundred years.

Mitigating train-induced building vibrations with rubber bearings designed for horizontal earthquake isolation

As rail transportation, including high-speed railways and urban metros, rapidly expands, its proximity to residential areas decreases, raising concerns about ground-borne vibrations. This study investigates the main characteristics of ground-borne vibrations induced by high-speed railways and metros through substructure method based on 2.5D FEM-MFS (finite element method-the method of fundamental solutions). Besides, the study also delves into the vertical vibration behaviors of buildings caused by train operations, evaluating the effect of laminated rubber bearings designed for horizontal seismic isolation on the train-induced building vibration mitigation. Our findings highlight that the broadband vibrations from train operations might coincide with the natural vibration frequencies of buildings, potentially leading to resonance. Implementing isolators allows the natural frequencies of the vibration modes with larger effective masses to be significantly lower than the dominant frequencies of train-induced ground-borne vibration, reducing the high-frequency responses. Additionally, the vibration mitigation enhances with the increase in the thickness of rubber layer. This research not only aims to reduce vibration levels in buildings adjacent to railways, enhancing the living conditions and health of residents but also underscores the engineering innovations necessary for sustainable urban development.

Analyzing the Influence of the Commuter Rail in Decongesting Roads in Nairobi

Nairobi, the capital city of Kenya is experiencing road traffic congestion which gets worse at peak times. Amongst, the interventions tried to help reduce the congestion is the introduction of commuter rail services. However, almost 11 years after commissioning the usage of the service is still very low and the roads are still experiencing congestion. The aim of this study is to determine the influence of the commuter rail service in decongesting the roads in Nairobi. The study made use of questionnaires to determine the stakeholders’ perception on the influence of travel cost, travel time, convenience and reliability in attracting them to the usage of the commuter rail. The results indicate a direct relationship on the influence of travel time, travel cost, convenience and reliability of the commuter rail to decongestion of roads. The improvement of the travel aspects of time, cost, convenience and reliability is expected to attract users to the commuter rail in effect reducing road transport users leading to less congestion on the roads

CFD Simulations to study the Effect of Ambient Temperature on the Ventilation in a Metro Tunnel under Different Heat Release Rate

Urban and inter-urban rail transport provide the most favoured commuting option for millions of individuals globally. In spite of massive investments of public money to develop rail technologies and related infrastructure such as tunnel systems, there remain challenges to ensuring safety in this area. Railway tunnels present specific and serious fire safety issues, based on their length and restricted width. Smoke and other emissions from fires are a central factor to be considered in relation to both structural safety and survival where tunnel fires occur. Patterns of smoke flow can impact upon how efficient exhaust systems are, and for naturally ventilated systems, establishing shaft smoke flow patterns in tunnel fires is a significant requirement. While earlier work has considered this issue, it has been based on standard atmospheric conditions, while external temperatures can influence smoke movement properties, heat distribution, and the pattern of smoke flows within vertically constructed shafts. This study takes the case study of an underground metro tunnel, applying computational fluid dynamics through ANSYS Fluent to simulate and examine the effects of more extreme external temperatures for fires of 5 and 15 mw occurring in this environment.

The Influence of CRTS II Slab Ballastless Track Upper Arch Deformation on the Wheel Jumping Law of High-Speed Vehicle

To study the impact of upwarp deformation in the ballastless track on the jumping behavior of the high-speed vehicle, utilizing UM and ANSYS joint simulation, a vertical vibration model of high-speed vehicle on CRTS II slab ballastless track was developed based on the non-Hertz wheel–rail contact model of virtual penetration theory. By using the single-wave cosine curve simulating the characteristics of upwarp deformation in the track slab, we calculated the whole process of wheel jumping. This allowed us to analyze how the amplitude and wavelength of the track slab upward deformation influence the vibration response of the vehicle–track system. Our findings indicate that when a wheel passes through the arch section of the track slab, the entire wheel jumping process consists of distinct stages: “wheel–rail bonding, wheel–rail separation, wheel–rail impact (one or more times), and wheel–rail bonding.” As the amplitude of upwarp deformation increases and the wavelength decreases, significant changes occur in several parameters, including the vertical force between the wheel and rail, wheel unloading rate, wheel jump height, frequency, duration, and vertical displacement of the rail. Additionally, when the wavelength is between 2 and 6[Formula: see text]m and the amplitude is 8[Formula: see text]mm, the vertical force between the wheel and rail becomes zero, the wheel load reduction rate is one, and the wheel jumps. When the wavelength is less than 3[Formula: see text]m, the wheel jump height exceeds the flange height, increasing the risk of derailment. Meanwhile, during the first wheel–rail impact, the wheel–rail vertical force and the rail vertical displacement reach their maximum, potentially impacting rail service performance negatively. Finally, compared to the amplitude of the track slab camber deformation, its wavelength has a greater impact on the entire process of wheel jumping. It is recommended that attention be paid to the change in the wavelength of the track slab camber during the maintenance and repair of the ballastless track.

MODEL OF FUNCTIONING LOGISTICS FOR SUPPLY OF SPECIALISED VEHICLES IN CONTAINERS FROM NORTH AMERICAN COMPANIES TO UKRAINE

The article analyses the current state and prospects for developing logistics for supplying various types of cargo in international traffic to be transported in containers. It allowed us to formulate the purpose of the study in this development. This topic is relevant since the efficient organisation of containerised supply logistics can improve the functioning of transport systems. An effective way to reduce the cost of supplying a cargo unit is efficient resource use (railway stations, ports, warehouses, wagons, vehicles, containers). The study paid considerable attention to developing the relevant infrastructure, solving specific problems of efficient use of all types of resources, using digital technologies, and building reliable models of logistics supply systems. The article builds a structural model based on the principles of logistics interaction of possible participants in the supply process, representing the interaction of subsystems that significantly affect the quality of the relevant operations. We formed five schemes of interaction between logistics participants for supplying specialised vehicles in containers with the participation of automobile, railway, and sea transport and the relevant infrastructure. These schemes identify the main ports of departure in the United States (New York and Houston) and ports of destination in Europe (Klaipeda (Lithuania), Constanta (Romania)), and take into account the possibility of using road and rail transport resources in European countries and Ukraine. We developed a mathematical model of logistics functioning for the supply of specialised vehicles in containers from North American enterprises to Ukraine, which accounts for the specifics of sequential operations and the peculiarities of determining the performance indicators of each supply chain operation. The prospect of using these models is to build a simulation model of logistics for the supply of specialised vehicles in containers from North American companies to Ukraine, conduct simulations using a software environment, and determine the rational option under the established conditions. Keywords: model, logistics, supply, vehicles, international transportation.

Optimal PV‐storage capacity planning for rail transit self‐consistent energy systems considering extreme weather conditions

AbstractWith the rapid development of electrified rail transportation, the traction load demand of rail transportation has increased sharply, and its operational security under extreme conditions has been highlighted. Given the above background, this paper proposes a planning method for the optimal photovoltaic (PV)‐storage capacity of rail transit self‐consistent energy systems considering the impact of extreme weather. First, the basic structure of a rail transit self‐consistent energy system is presented. Second, considering a power transmission system with line trip‐off under extreme weather conditions, a traction load reduction model is established to obtain the maximum power exchange capability between the power transmission network and rail substations. Subsequently, an optimal planning model for a hybrid energy storage system (HESS) is proposed to minimize the total HESS investment and rail transit system operation costs. Finally, the model is linearized as mixed‐integer linear programming and solved using Gurobi and the Yalmip toolbox. The simulation results verify the effectiveness of the proposed optimal PV‐storage capacity planning for rail transit self‐consistent energy systems.

A step-by-step experimental characterization of a low-height acoustic barrier for railway applications

ABSTRACT The development of rail transport is crucial for transitioning towards a more sustainable form of mobility. It is imperative to address and mitigate issues regarding discomfort and noise pollution caused by rail traffic in order to foster a harmonious coexistence between the population and railway transport. In this paper, an experimental prototype of a low height acoustic barrier is characterized. The barrier has a high capacity for mitigating railway noise and has great potential for urban design. The acoustic barrier prototypes were initially developed using numerical models and subsequently subjected to a series of experimental tests. The initial experimental characterization was carried out in a semi-anechoic chamber. In the second phase, the prototypes were tested in a free field. The final phase of the experimental characterization involves the application of the noise barrier prototypes along a section of the Sintra railway line, located near Lisboa, Portugal. The results demonstrate the significant potential for noise mitigation offered by the developed solutions, achieving insertion loss levels of approximately 10 dB across the entire frequency range.

Event-driven piezoelectric energy harvesting for railway field applications

Piezoelectric energy harvesters (PEHs) hold promises for revolutionizing railway structural health monitoring (SHM). However, the challenges of designing high-robust PEHs for handling complex and ever-shifting vibrations in practical railway scenarios remain formidable. Unlike conventional methods that align the fundamental frequency of the PEH with the dominant frequency of the vibration source, this study employs an event-driven enhancement method. This study commences by employing a high-fidelity dynamic model of the PEH and an advanced vehicle-track coupled dynamic model to evaluate energy harvesting efficiency across various railway scenarios. The vehicle-induced track vibrations are predicted across various train speeds, track structures, and track irregularities, considering 12 distinct vehicle-track conditions and totaling 3600 simulation datasets, each representing a specific event. We employ the particle swarm optimization (PSO) algorithm to identify optimal PEH designs for different events. To streamline this process, instead of offering one optimal solution for each event, we employ the K-means algorithm to cluster similar events. Subsequently, we choose the centroid design for each cluster as the representative solution for events within that cluster. This approach allows us to use a limited number of representative PEHs to effectively address most events across different clusters. Finally, we thoroughly examine and evaluate the dynamic responses of these representative designs to demonstrate their robust performance. This study explores PEH design optimization from a fresh perspective, bridging the gap between theoretical design and practical implementation in rail transportation systems.

The Analysis of Passenger’s Facilities Level of Service on Jakarta - Bogor Commuter Line’s Stations Using PTV Viswalk

To accommodate the increasing number of passengers of DKI Jakarta which is Indonesia’s economic center, largely relies on public transit, notably rail transportation. Data on volume, density, speed, annual passenger volume, and passenger growth projections for the following ten years are needed to evaluate passenger’s facilities level of service in platform area based on Ministerial Regulation No. 29/PRT/M/2011 concerning the Technical Construction of Railway Stations and the Highway Capacity Manual of 2006. The Level of Service (LOS) is then calculated from the data using PTV Viswalk software, which evaluates passenger traffic and density. The results of the PTV Viswalk software is validated by the Geoffrey E. Havers (GEH) test and the maximum passenger density to determine the Level of Service (LOS). All stations’ service levels lie between LOS C and LOS F with varying space modulus values. A solution for the rise in passengers over a decade is multi-story development.

Investigating influential factors on railway passenger flow utilizing multi-source data fusion and flow space theory: A case study of the Yangtze River Delta megalopolis, China

Employing flow space theory and multi-source data, this study examines the spatial network structure and factors influencing railway passenger flow, which is crucial for rail planning in densely populated megalopolises. Focusing on China's Yangtze River Delta (YRD) megalopolis, we utilize social network analysis to explore the characteristics of various flow networks and their interactions with the railway passenger flow network. Our key findings include the following: (1) A pronounced polarization effect and core-periphery structure exist in the YRD, notably within industry and railway flow networks; (2) Industry and corporation flow significantly contributes to rail passenger flow, with corporation networks in commerce, technical services, and finance showing higher similarity to the railway passenger flow network; (3) There is significant heterogeneity in the correlation between rail passenger flow and other flows within sub-networks formed by connections among nodes of different levels. (4) Enhancing railway services at lower-level nodes is essential to mitigate the disparity between population mobility and rail passenger flow, and to promote rail transportation equity. This research offers valuable insights for policymakers in developing countries to strategically plan railroad networks in megalopolises.

Artificial Intelligence in Regenerative Braking for Trains: A Systematic Review

The impact of Artificial Intelligence (AI) on different sectors, including railways, is now widely recognized. This paper shares the findings of a comprehensive literature review on how AI affects regenerative braking in railway transportation. The review focuses on various areas of regenerative braking, such as energy storage system, timetabling, and reversible substation.
 In the literature review, it was found that 57 scientific papers were published from 2017 to December 2022. The majority of these papers, specifically 70.2%, utilized AI to optimize the effectiveness of regenerative braking. However, the use of AI in reversible substation and a combination of methods for regenerative braking is still limited, even though several methods exist. With the continuous development of new AI innovations, it is anticipated that new strategies will be created to enhance energy efficiency in regenerative braking, particularly in rail transportation.
 Keywords: Artificial Intelligence, Regenerative Braking, Railway.

INTERNATIONAL COMPETITIVENESS OF UKRAINE IN THE FIELD OF RAIL TRANSPORT

The purpose of this article is to determine the competitive position of Ukraine in the field of railway transportation in comparison with Poland (a neighbouring country), Switzerland (a benchmark in the field of railway transportation) and Canada (which professes a completely different “American” principle of operating railway networks, where freight transportation is a priority). Methods. In the process of working on the article, the following research methods were used: analysis and synthesis in the selection of indicators and their grouping (production and financial, scientific and technical development, personnel characteristics) depending on the direction they characterise; methods of economic analysis – multidimensional comparative analysis, index analysis, Delphi method in determining the weight of indicators selected for analysis, rating to determine the final positions of each of the countries selected for analysis. Results. Among the main results of the study is the determination of Ukraine’s competitive position, primarily in comparison with Poland as a neighbouring country. The next most important is the group of indicators that put Ukraine behind the Swiss railways’ benchmarks, in particular, the quality of infrastructure and electrification. The scientific novelty of the results obtained is an attempt to assess the competitive positions of railway transport, which seemingly cannot compete with each other, since each of them operates in a separate territory (in most cases within the same country) and their interests hardly overlap. Currently, this is not entirely true, since, after the large-scale invasion, due to the blockade of Ukrainian seaports, a significant part of export and import commodity flows has moved to rail transport, and by analysing the situation in each individual transit country, it is possible to choose the direction that will be most acceptable for the long-distance transportation of goods to “third” countries. The practical significance of the results obtained can be viewed from at least two perspectives. The first is the indicators that have caused the Ukrainian railway to lag behind the benchmark state (Switzerland) and the work to improve the situation in each of the areas. The second side is the possibility of conducting a similar assessment of the situation in rail transport among all of Ukraine’s neighbouring countries and identifying the highest priority areas for sending most of the export and import cargo to “third” countries.

The dynamics of port competition and efficiency in Vietnam amidst COVID-19: a decadal analysis

Vietnamese seaports play an important role as crossroads for import, export and transformation in delivery from maritime transport to rail, road and inland waterway transport. Over the last two decades, the seaport system has been reformed with the participation of private and foreign investors. Consequently, this issue enhances competition between seaports and brings changes to the seaports’ operations. In this article, the relationship between seaport competition and efficiency is examined in the context of Vietnam, an emerging market economy. The longitudinal data from 2011 to 2022 is collected to quantify the competition degree of Vietnamese seaports and Data Envelopment Analysis is used to measure seaport efficiency. A number of measures are used to quantify the competition level of the seaport system over time, including concentration ratio, Gini index, and Hirschman-Herfindahl Index. Besides, market share at both national and regional levels and distance to the nearest competing seaport are criteria of port-level competition. The results advocate an increasing trend of seaport competition in Vietnam. Moreover, based on Tobit regression models, the competition among seaports relates positively to efficiency using both the 2021-2022 and 2015-2016 data sets. Under the COVID-19 pandemic, the impact of external factors on seaport efficiency is insignificant and inconsistent due to the disruption of logistics systems and disrupted links to the outside environment.

PARTICIPATION OF FOREIGN CONTRACTORS IN PUBLIC TENDERS BY PKP POLSKIE LINIE KOLEJOWE S.A. BETWEEN 2021 AND 2022

The participation of foreign contractors in public procurement is indicative of the openness of a given economic system to external competition. Operating networks that provide rail transportation services to public entities is subject to sector-specific regulations for public procurements. Construction works in the railway engineering segment represent lucrative contracts, and their outcomes hold strategic significance for society and the economy. PKP Polskie Linie Kolejowe S.A., the national operator of railway lines, is a key player in the sectoral public procurement market in Poland. Upon analysing the participation of foreign contractors in the above company’s tender proceedings, it becomes possible to identify the strategies utilised by economic entities from outside the public funds holder’s territory to apply for public procurement.