Correction: On the right track: psychosocial hazards and well-being in freight train driving

ABSTRACT As a crucial component, the condition monitoring of wheel-axle bearings of heavy haul freight trains is of significance. However, due to the influence of the number of real fault samples and complex operating conditions, the accuracy of the current algorithm still needs to be improved. To tackle the problem, a framework for diagnosing the bearing faults of heavy haul freight trains is proposed, based on an adaptive multi-scale Laplace wavelet module (MLWCL) and a multi-channel weighted fusion strategy. Firstly, MLWCL is devised to address the issue of indistinct features of real signals with noise. The input signal is divided into groups of different sizes, which are analyzed from different MLWCL analysis scales. Meanwhile, in order to solve the problem of the exponential component in Laplace wavelets affecting the initial value distribution of the model, a suppression function is proposed. The suppression function avoids edge perception decline by adaptively adjusting the extremum points to match the Laplacian median points. Finally, a multi-channel weighted fusion layer enhances impact signal perception by fusing global trend features and local detail features. Experiments on the dataset collected from real faulty heavy train bearings demonstrate that the model possesses excellent generalisation and anti-noise robustness.

Research on train aerodynamics has so far mostly focused on high-speed passenger trains. However, increasing evidence is being acquired showing that aerodynamic effects are also highly relevant to freight trains regarding their efficient and safe operation. Freight-train-specific aerodynamic phenomena become more relevant in light of the increase in freight train service speed expected to take place in the near future. For some decades now, experimental and numerical studies have been published about the aerodynamics of freight trains, and specifically of container trains. An overview of this effort is presented in this paper, the major points of agreement are summarized, and the open points in the field are identified. In the paper, the topology of the flow and the slipstream are described and their implications on the aerodynamic forces (both with and without crosswinds) are discussed. Special attention is given to aerodynamic resistance, drag and to the efforts made in literature to predict it using numerical and experimental methods. Furthermore, a comparison of the methods of investigation adopted in the field is presented, highlighting their suitability for the study of different problems. Finally, other topics like the risk for bystanders caused by slipstream effects, ballast flight and aerodynamics in tunnels are discussed. The literature review highlights the need to expand the research on freight train aerodynamics to freight train geometries different from intermodal container trains and to consider the many diverse geometries that may result from realistic mixed compositions of different wagon types.

The global shift towards cleaner energy sources is driving the adoption of hydrogen as an environmentally friendly alternative to fossil fuels. Among the forms currently available, Liquid Hydrogen (LH2) offers high energy density and efficient storage, making it suitable for large-scale transport by rail. However, the flammability of hydrogen poses serious safety concerns, especially when transported through confined spaces such as railway tunnels. In case of an accidental LH2 release from a freight train, the rapid accumulation and potential ignition of hydrogen could cause catastrophic consequences, especially if freight and passenger trains are present simultaneously in the same tunnel tube. In this study, a three-dimensional computational fluid dynamics model was developed to simulate the dispersion and explosion of LH2 following an accidental leak from a freight train’s cryo-container in a single-tube double-track railway tunnel, when a passenger train queues behind it on the same track. The overpressure results were analyzed using probit functions to estimate the fatality probabilities for the passenger train’s occupants. The analysis suggests that a significant number of fatalities could be expected among the passengers. However, shorter users’ evacuation times from the passenger train’s wagons and/or longer distances between the two types of trains might reduce the number of potential fatalities. The findings, by providing additional insight into the risks associated with LH2 transport in railway tunnels, indicate the need for risk mitigation measures and/or traffic management strategies.

Energy self-contained freight train monitoring system with cooperative wind and vibration energy harvesting

ABSTRACT Effective monitoring of the air brake system is of paramount importance, as early fault detection can prevent severe failures. Despite the progress made in Condition Monitoring (CM) and Condition-Based Maintenance (CBM) for freight train brake system, current solutions face several challenges in detecting two major malfunctions: air brake leakages and manual brake activation. Existing methodologies for fault data collection are hindered by key limitations: reliance on simulations or test rigs that do not fully capture real-world operating behaviour, employment of non-optimized monitoring system tailored to the specific application and lack of robust validation under realistic conditions. This paper presents an innovative methodology to address these gaps by integrating model-based fault injection for monitoring system design, custom fault injection devices for controlled fault reproduction on full-scale freight wagons and experimental validation in real-world condition. The latest has been carried out on the closed-circuit test of San Donato where air brake leakages and manual brake activation have been systematically simulated under varied test scenarios including different train speed, braking action, brake mode, and wagon loading. The results indicate that the maximum brake cylinder pressure is a reliable indicator of combined leakages during service and emergency braking, whereas the pressure build-up gradient proves effective in detecting both manual brake activation and combined leakages during service and emergency braking in freight mode. The proposed methodology provides a scalable and reliable foundation for real-world deployment and data collected through the field validation represents a highly valuable fault dataset for the future advancement of diagnostic algorithms.

As an innovative approach to easing megacity congestion and boosting transport efficiency, subway freight transportation can enhance rail utilisation, accelerate logistics, and reduce pollution. First, from the perspective of passenger and cargo safety, a model with the objective function of maximising cargo passage efficiency was constructed to derive the optimal path for cargo entry into the station. Then, targeting minimal enterprise costs, with hourly granularity, optimisation models for train operation plans were formulated under three modes: passenger-cargo co-compartment, passenger-cargo co-train with separate compartments, and dedicated freight trains, leveraging the estimated remaining cargo capacity and predicted demand along the routes. Finally, a case study on Shanghai Metro Line 9 was taken to demonstrate the proposed approach, it can effectively tap the remaining transport capacity of subways during specific time periods, lower enterprise costs, ensure efficient operation of passenger and freight flows, and alleviate urban traffic and environmental pressures.

Abstract An in-depth investigation of the freight train industry from the perspective of understanding their interconnected psychosocial work environment for better work design is crucial yet scarce. In this study, we aimed to investigate and identify the psychosocial work environment of freight train drivers and define the key psychosocial hazards they encounter, impacting their well-being and professional domain. The investigation was conducted on a total of 532 German freight train drivers. Corresponding to the theory of healthy work design, exploratory factor analyses of the Copenhagen Psychosocial Questionnaire identified a three-dimensional factor loading. A random forest model was calculated, showing emotional demands, social relations, commitment, and variables of job control to be key factors in the interwoven psychosocial work environment of freight train drivers. Understanding and building scientific understanding of these predictors would explain the impact of each predictor on the factors contributing to and asserting occupational safety. We discuss our findings considering existing literature and consequences for better work design.

Analysis of freight train passing a stop signal using machine learning: Application of XGBoost and SHAP

Globally, noise pollution has become an emerging problem, especially due to transportation. Railway noise is overlooked among different types of transportation noise, which creates an environmental issue that disproportionately affects vulnerable communities. This study was conducted on slum settlements situated on empty land near rail track areas, which is frequently neglected in previous research despite their high exposure risks. This study examines variations in noise levels across passenger and freight trains, including subcategories (express and superfast) of passenger trains powered by diesel and electric locomotives, by monitoring 1057 pass-by trains through the 14 locations in urban slums of Delhi, India. Noise levels were monitored using a type I sound level meter, and statistical analysis was conducted along with graphical representation to understand its spatial and categorical variations. The results showed that diesel engine trains were consistently noisier than electric engine trains, with approximately 2-8dB higher levels. Freight trains were identified as the loudest contributors, generating a mean noise of 100.1dB, found approximately 8dB higher than passenger trains. Spatial analysis revealed significant variation in noise, with the highest and lowest mean difference observed at locations L11 and L6, 47.0dB and 32.5dB, respectively, which violated the prescribed limit set by CPCB at all sites. A strong link between the train frequency and noise level (LAT) was observed in the temporal and statistical analysis, especially during peak afternoon hours. Using the IDW interpolation, GIS-based mapping identified the spatial hotspots, which will support making time and location-specific mitigation measures. These insights emphasize the need to enforce noise abatement measures and implement sustainable rail practices to attenuate the excessive noise burden on these slum communities.

Abstract A slight slip on the wheel/rail contact surface during the hunting motion will cause the temperature on the interface to increase, which will influence the contact characteristics and lifespan of the wheel/rail materials. For the purpose of investigating the thermo-mechanical coupling effect of wheel/rail contact during the hunting motion and its influence on the wheel/rail contact characteristics, a three-dimensional (3D) full-size finite element model for the thermo-mechanical coupling of wheel and rail is constructed using Ansys software according to the actual size. The model includes the wheel, rail, pad, sleeper, and foundation system. The wheel/rail contact characteristics, temperature, stress and strain distribution under different creep states of train (lateral creep, longitudinal creep, and spin creep) are researched for freight train travelling at a speed of 40 km/h. The study indicates that the initial contact patch shape of wheel/rail is similar to an ellipse, with an area of 164.3 mm2. The lateral creep and longitudinal creep have a significant effect on the temperature. The temperature distribution is sinusoidal waveform, and the longitudinal creep can lead to a temperature rise of up to 58.6 ℃. The spin creep has a little effect on the temperature, stress and strain. During lateral slipping, the contact patch transitions from an elliptical shape to a circular one, and then back to an ellipse. This transformation has a considerable impact on the contact area, maximum contact stress, and its location.

The train slipstream, referring to the air velocity induced by the train, significantly impacts the safety of passengers and track workers. While extensive research examined slipstream effects in open air, fewer studies address their behavior in tunnels. This study bridges the gap through a full-scale experimental campaign analyzing slipstream effects for high-speed, conventional, and freight trains in both open air and tunnel environments. The results reveal substantial differences in slipstream behavior. In open air, airspeed increases steadily around the train, creating smoother airflow transitions. Conversely, tunnels amplify slipstream effects due to confinement, with stronger wind peaks near the train nose caused by piston and blockage effects. High-speed and conventional trains generate notable backflow between tunnel walls and the train, absent in open air, whereas freight trains exhibit limited backflow due to their highly turbulent flow. A statistical analysis of maximum airspeed peaks shows velocity fluctuations 10%–30% higher in tunnels for passenger trains on specific sides, causing potential risks for platform users, while freight trains display variable trends influenced by tunnel geometry. This study underscores the amplified slipstream effects in tunnels and the need for enhanced safety measures, and highlights the need to develop future research based on numerical methods to expand the understanding of slipstream effects in tunnels.

ABSTRACT This article explores how Małaszewicze, a small locality in Eastern Poland, is deeply entangled with China’s global ambitions. Positioned at the European Union border, Małaszewicze is home to one of Europe’s largest dry transhipment ports. It is an obligatory stop for freight train connections labeled “China-Europe Railway Express” and an important node in the Belt and Road Initiative (BRI). Drawing from material collected between 2021 and 2023, I anchor Małaszewicze in wider debates about China’s global expansion, contributing to the growing literature that localizes and provincializes Global China and explores local agency within the BRI. I outline various strategies that local actors in Małaszewicze employ to capture the global potential of the port infrastructure: amplifying the narrative that frames their locality as central to Europe-Asia trade, bringing symbolic evidence from interactions with Chinese actors, and putting pressure on national-level institutions through repeated visits to Warsaw. I demonstrate how the BRI empowers local actors to claim their community’s right to modernity by shifting it from Europe’s peripheries toward the center of the Global East. However, the strategy of aligning local development with the BRI comes with inherent vulnerabilities, increasing the exposure to geoeconomic dynamics that unfold far beyond local control.

Minimizing wind power plant imbalances using freight train gravity energy storage and intraday forecast updates

High-speed railway (HSR) has significant potential for express freight transportation, particularly for postal and parcel delivery, owing to its speed, reliability, and environmental benefits. However, existing approaches, primarily relying on mixed passenger–freight trains, are limited in addressing large-scale express demands. This paper proposes a novel optimization framework for integrating postal and parcel delivery into HSR systems, combining passenger services with dedicated express operations. The framework includes: (1) a express distribution model to maximize the utilization of existing mixed trains; (2) a dedicated express trains candidate set generation model for dedicated express trains, minimizing operational and environmental costs through optimized routes and stop plans, and the column generation algorithm is used to decompose and solve to obtain the dedicated express train candidate set; (3) an express distribution model to achieve precise matching between dedicated express trains and express shipments. A case study on the Beijing–Guangzhou HSR corridor demonstrates the method’s effectiveness, achieving precise distribution of express, reducing operational costs, and improving train load efficiency. This study provides actionable insights for scaling up postal and parcel delivery using HSR, addressing the gap in the integration of freight and passenger services within sustainable railway logistics.

To address the low accuracy and poor generalization of existing brake chain anomaly detection algorithms for freight trains in complex scenarios, this paper proposes an improved You Only Look Once version 11-based real-time image detection framework. The simple attention module is integrated into the backbone network to enhance feature extraction, while the content-aware reassembly of features up-sampling operator improves texture reconstruction of brake chains, particularly for small targets like lock chains. A dynamic wise intersection over union loss function with adaptive non-monotonic focusing weights is designed to mitigate localization errors caused by complex backgrounds. Experiments on a self-built dataset (2,000 linear array images) show that the improved model achieved a 99.5% mean average precision on the test set, a 5.4% increase over baseline You Only Look Once version 11, with single-frame inference time of 12.9 ms. This method enables real-time, high-precision detection of brake chain tightness, offering a lightweight solution for intelligent safety monitoring in freight train operations.

Abstract Replacing the energy density and convenience of diesel fuel for all forms of fossil fuel-powered trains presents significant challenges. Unlike the traditional evolutions of rail which has largely self-optimised to different fuels and cost structures over 150 years, the challenges now present with a timeline of just a few decades. Fortunately, unlike the mid-1800s, simulation and modelling tools are now quite advanced and a full range of scenarios of operations and train trips can be simulated before new traction systems are designed. Full trip simulations of large heavy haul trains or high speed passenger trains are routinely completed controlled by emulations of human drivers or automated control systems providing controls of the “virtual train”. Recent developments in digital twins can be used to develop flexible and dynamic models of passenger and freight rail systems to support the new complexities of decarbonisation efforts. Interactions between many different traction components and the train multibody system can be considered as a system of systems. Adopting this multi-modelling paradigm enables the secure and integrated interfacing of diverse models. This paper demonstrates the application of the multi-modelling approach to develop digital twins for rail decarbonisation traction and it presents physics-based multi-models that include key components required for studying rail decarbonisation problems. Specifically, the challenge of evaluating zero-emission options is addressed by adding further layers of modelling to the existing fully detailed multibody dynamics simulations. The additional layers detail control options, energy storage, the alternate traction system components and energy management systems. These traction system components may include both electrical system and inertia dynamics models to accurately represent the driveline and control systems. This paper presents case study examples of full trip scenarios of both long haul freight trains and higher speed passenger trains. These results demonstrate the many complex scenarios that are difficult to anticipate. Flowing on from this, risks can be assessed and practical designs of zero-emission systems can be proposed along with the required recharging or refuelling systems.

Compared to road trucks, the use of trains to move goods along railway lines is a more sustainable freight transport system. In Norway, where several main lines are single tracks, the insufficient length of many of the existing passing loops considerably restricts the operational and economic benefits of long trains. This brief technical note revolves around the possible upgrade of the Røros line connecting Oslo and Trondheim to accommodate 650 m-long freight trains as an alternative to the heavily trafficked Dovre line. Pivoting on regulatory standards, this exploratory work identifies the minimum set of infrastructure modifications required to achieve the necessary increase in capacity by extending the existing passing loops and creating a branch line. The results indicate that 8 freight train routes can be efficiently implemented, in addition to the 12 existing passenger train routes. This brief technical note employs building information modeling software Trimble Novapoint edition 2024 to position the existing railway infrastructure on topographic data and visualize the suggested upgrade. Notwithstanding the limitations of this exploratory work, dwelling on capacity calculation and the design of infrastructure upgrades, the results demonstrate that modest and well-placed interventions can significantly enhance the strategic value of a single-track rail corridor. This brief technical note sheds light on the main areas to be addressed by future studies to achieve a comprehensive evaluation of the infrastructure upgrade, also covering technical construction and economic aspects.

Abstract The purpose of this research is to analyze Dacia’s AILN (Alliance International Logistics Network) performance metrics and provide an overview of its main distribution centers (via road haulage, rail freight and sea shipping) and the operational logistics challenges faced by its supply chain alternatives. Other research articles deal with issues of logistics operations and/or supply chains of either one particular manufacturing facility (partial optimization) or focus on topics like sustainability, network optimization (re)design and/or resilience strategies to reduce specific automotive industry risks, providing less applicable solutions (overly broad). Relevant production, sales and distribution data (capacities, volumes and lead times) is analyzed at Dacia’s main plants in the last 10 years (2015-2024) using quantitative and qualitative methods to provide a comprehensive overview of its logistics competitiveness. The case study’s main results show an accelerated sales growth in the last 20 years with over 90% of vehicles being exported, whilst the top 5 international markets account for over a half of Dacia’s total sales volumes. Dacia’s AILN handles outbound logistics operations of assembled vehicles as well as shipping parts to other Renault or Nissan manufacturing sites through Constanta Port (TEU containers), Curtici Cargo Center (freight trains) and Nadlac II border crossing (car-carrying trailers). Heavy road traffic and congestion, low average speed and inconsistent reliability of freight trains, as well as lengthy loading times of ships affect delivery lead times which can reach 30-45 days, on average. The paper highlights practical insights of Dacia’s complex logistics and supply chain management challenges, sourced from automotive industry professionals, adding a real-life impact to the research findings.

Many train positioning technologies utilizing remote vibroacoustic sensing rely on frequency-based and threshold-based signal analysis methods. The vibroacoustic signal propagating through optical fibers laid along railway tracks suffers from significant contamination by external noise, leading to substantial positioning inaccuracies. Consequently, developing a method to accurately localize moving railway vehicles with desired precision remains a critical challenge. The aim of the study is to develop an effective method for processing and analyzing vibroacoustic signals to enable positioning of a moving railway trains with the required accuracy. Materials and methods. The study was conducted using vibroacoustic signal recordings generated by freight trains exceeding 800 meters in length traveling along a 42 km railway section. This section is equipped with a vibroacoustic sensing system. For processing the vibroacoustic signals, the difference method, fast Fourier transform method, and grayscale image segmentation techniques were employed. The original signal was pre-filtered using the difference method. Subsequently, a fast Fourier transform method was applied along the time axis, followed by the calculation of the normalized sum of the discrete fast Fourier transform amplitude moduli. The resulting two-dimensional array of spectrograms was represented as an image. The task of identifying train boundaries was reduced to selecting a threshold that would separate the image into two classes: “train” and “background”. As the threshold value was chosen the one at which the inter-class variance between “background” and “train” reached its maximum. Results. Based on the unique frequency characteristics of each railway rolling stock, an algorithm has been developed to determine the real-time location of moving trains. The applied non-parametric threshold selection method enables the evaluation of threshold optimality using current data without requiring additional input parameters. The process begins with filtering the original reflectograms by calculating the difference between adjacent traces. This step is essential for removing static noise. Next, a time-domain fast Fourier transform is performed followed by the computation of the normalized sum of fast Fourier transform amplitudes. By treating the fast Fourier transform result as an image (where pixels represent normalized sums of absolute amplitudes from the discrete fast Fourier transform for each fiber optic sample), an image segmentation method can be applied to separate the “background” and “train” classes. The method relies on calculating an optimal threshold that maximizes the inter-class variance between “background” and “train”. During the comparison of each pixel’s brightness with the derived threshold, pixels are assigned values of 0 or 1, producing a binary array. Post-processing is then applied to the binary array, where all isolated 1s are set to 0. Subsequently, train boundaries are determined: the left boundary is identified as the first 1 from the start of the binary array, and the right boundary is the first 1 from the end of the array. To smooth the train boundaries, a least squares approximation method is applied. Using the proposed method on processed reflectogram recordings, the boundaries of moving trains along a railway section were identified with a deviation of within 20 meters. Conclusions. The proposed algorithm enables the positioning of both passenger and freight railway trains, including those composed of mixed carriages. Freight trains exhibit a higher susceptibility to wheel pair defects, which introduce distortions into vibroacoustic signals. Processing vibroacoustic signals in the frequency domain and analyzing a specific frequency range characteristic of moving trains mitigates the described effect, as well as dynamic environmental factors. The use of a non-parametric method for threshold calculation allows evaluating the optimality of the selected threshold value based on the criterion of maximum variance between the “background” and “train” classes. Computing frequency characteristics at equal short intervals during train movement enables adaptation to the current conditions of the railway track section.