Risk Of Derailment Research Articles

Analysis of 3k Experiments Applied to Railway Braking: Influence of Contaminants and Train Speed

The presence of contaminants influences braking efficiency in the railway system because it alters the adhesion at the wheel–rail interface. It is essential to study this phenomenon, as contaminants reduce the friction between wheels and rails, which impacts braking and transport safety. In addition, these contaminants increase the risk of derailments. The objective of the research was to determine the impact of different contaminants and operating speeds on the critical braking system’s responses. Using the 3k full factorial experimental design methodology, with analysis of variance (ANOVA) and linear and quadratic regressions, visualized using surface graphs, the effects of three operating conditions were studied: clean rails, with sand and sawdust, and driving the train at three operating speeds. These conditions gave rise to variations in braking distances, maximum creep, wheel slip times, and maximum peaks of electric current when braking in each experiment. The tests were carried out on the straight section of a β-shaped track and a railway vehicle, designed at a scale of 1:20. The analysis reveals that the braking distance increases significantly with surface roughness (clean track < sawdust < sand). At 0.75 m/s, the sawdust track reduces braking distance by 21% compared with the clean track; at 1.00 m/s, the reduction is 19%; and at 1.30 m/s, it is 35%.

A parametric approach for enhancing the accuracy of instrumented wheelset: A case study

The instrumented wheelset (IWS) is the most commonly used wheel-rail force test method, playing a crucial role in assessing the risk of derailment of railway vehicles. To enhance the accuracy of IWS, the study first investigates error sources and addresses the importance of eliminating the errors caused by contact point shift and wheel rotation. Functions related to the angular and radial position of strain gauges, the wheel-rail force amplitude and the wheel profile have been obtained. Parametric models for IWS error estimation have been established and used to transform the problem into an objective optimisation problem. Validation through a case study using Particle Swarm Optimization with nonlinear constraints has confirmed the model’s convergence and stability. Comparative analysis, alongside stationary test, demonstrated a significant reduction in crosstalk and ripple errors, verifing the method’s effectiveness in enhancing the accuracy of wheel-rail force measurement.

Study on the allowed maximum amplitudes of low-order polygonal wear on resilient wheels based on operational safety

Following the extensive use of resilient wheels on trams, several subways in China have started pre-launch testing of resilient wheels. While it remains at an early stage, the long-term behavior of the wheel has become a great concern for subway operators and wheel suppliers. To address the concern, this study focuses on derailment risk by evaluating the allowed maximum amplitudes of low-order polygonal wear on resilient wheels. Firstly, a metro vehicle-track dynamic system model equipped with resilient wheels is built. Then, based on the operation safety index and current re-profiling regulations for conventional wheels, the influence of wheel axial and radial stiffness on the radial amplitude limits of resilient wheel polygonal wear is analyzed. To perform the analysis, firstly the commonly-used stiffness for a resilient wheel (300 kN/mm in radial direction and 50 kN/mm in axial direction) is adopted to study the effect of resilient wheel polygonization on wheel load reduction ratio. Then, wheel load reduction ratio is predicted for different radial (up to 600 kN/mm) and axial (up to 100 kN/mm) stiffnesses of the resilient wheel and different orders (up to 10) of wheel polygonization of 1 mm amplitude. A contour plot is provided to illustrate how the wheel load reduction ratio varies with the harmonic order and amplitude of wheel polygonization under different combinations of resilient wheel’s equivalent axial and radial stiffnesses. It is found that, with the increase of the amplitude of the polygonal wear of a certain harmonic order on resilient wheel, the number of the available combinations of the equivalent stiffnesses adopted by the resilient wheel becomes less by considering the operation safety indexed with wheel load reduction ratio. Besides, depending on the stiffness of the resilient wheel, the allowed amplitude corresponding to the polygonization of each order has been suggested with the contour plots.

Research on the Risks and Preventive Measures of Ideological and Political Education for College Students in the Context of the Internet

In the internet context, education’s pertinence and timeliness have been significantly improved. However, the online world is also full of hidden risks, and in this context, the behavior and thoughts of college students may have the risk of derailment. At the same time, the implementation of ideological and political education in universities may also face challenges. This article will analyze the causes of risks faced by ideological and political education for college students from three different perspectives: online media, individual students, and university management. In the final part of the article, targeted suggestions will be proposed, including strengthening student risk awareness education, enhancing the discourse power of universities in ideological and political education, and fully utilizing the advantages of online tools to increase risk prevention efforts, adapt to new changes in the online environment, and lead the new direction of university education work.

Integrating Machine Learning in Geotechnical Engineering: A Novel Approach for Railway Track Layer Design Based on Cone Penetration Test Data

The cone penetration test (CPT) has emerged as a cost-effective and time-efficient method for assessing soil conditions relevant to railway track infrastructure. The geotechnical data obtained from the CPT serve as crucial input for asset managers in designing optimal sublayers and form layers for track renewal works. To properly assess the condition of soil layers, various soil behavior type charts and machine learning models based on CPT data have been published to help engineers classify soils into groups with similar properties. By understanding the properties of the soils, an optimal substructure can be designed to minimize extensive maintenance and reduce the risk of derailment. However, when analyzing multiple CPTs, the diversity and non-uniformity of subsoil characteristics pose challenges in designing a new optimal trackbed. This study presents an automated approach for recommending thicknesses of sublayers and form layers in railway tracks based on CPT data, employing machine learning algorithms. The proposed approach was tested using CPT data from the Belgian railway network and showed very good agreement with results from traditional soil investigation interpretations and layer design. A Random Forest classifier, fine-tuned through Bayesian optimization with a cross-validation technique and trained on 80% of the datasets, achieved an overall accuracy of 83% on the remaining 20%. Based on these results, we can conclude that the proposed model is highly effective at accurately designing sub-ballast layers using CPT data.

The Influence of Seasonal Effects on Railway Vertical Track Modulus

Adequate vertical track support is essential for safe and efficient railway operations. Insufficient support leads to distorted track geometry, increased dynamic loads, component stress, poor ride quality, rolling stock damage, and derailment risks. Current inspection practices focus on assessing the condition of the track components and geometry, rather than the root causes of degradation. To improve this condition, this study presents the use of a methodology that utilizes an autonomous vertical track deflection measurement system mounted on a loaded rail car (36 tonnes/axle) to support track maintenance decisions in a heavy haul railroad located in southeast Brazil. The system continuously measured substructure stiffness along the railway line. Over one year, data were collected from over 8000 km of track. The study highlighted seasonal effects on track degradation over time, identifying areas with significant deflections and high deflection rates, which contribute to issues such as differential settlement and reduced lifespan of track components. Additionally, the study revealed seasonal effects, with deflections peaking during wet weather and decreasing during dry cycles. A method to classify weak track areas was developed, facilitating monitoring and enabling more effective maintenance planning, contributing to the reduction of overall track maintenance costs and enhancing safety and operational efficiency.

Running safety assessment method of trains under seismic conditions based on the derailment risk domain

The accurate assessment of running safety during earthquakes is of significant importance for ensuring the safety of railway lines. Currently, assessment methods based on a single index suffer from issues such as misjudgment of operational safety and difficulty in evaluating operational margin, making them unsuitable for assessing train safety during earthquakes. Therefore, in order to propose an effective evaluation method for the running safety of trains during earthquakes, this study employs three indexes, namely lateral displacement of the wheel–rail contact point, wheel unloading rate, and wheel lift, to describe the lateral and vertical contact states between the wheel and rail. The corresponding evolution characteristics of the wheel–rail contact states are determined, and the derailment forms under different frequency components of seismic motion are identified through dynamic numerical simulations of the train–track coupled system under sine excitation. The variations in the wheel–rail contact states during the transition from a safe state to the critical state of derailment are analyzed, thereby constructing the evolutionary path of train derailment and seismic derailment risk domain. Lastly, the wheel–rail contact and derailment states under seismic conditions are analyzed, thus verifying the effectiveness of the evaluation method for assessing running safety under earthquakes proposed in this study. The results indicate that the assessment method based on the derailment risk domain accurately and comprehensively reflects the wheel–rail contact states under seismic conditions. It successfully determines the forms of train derailment, the risk levels of derailment, and the evolutionary paths of derailment risk.

An Approach for Real-Time Monitoring of Train Derailments: An Impact-Based Monitoring Method

Train derailments are severe incidents in rail transportation, posing significant risks to passenger safety and infrastructure integrity. However, the excessive lateral vibrations of the wheelset, which are a direct cause of derailments, often cannot be effectively monitored and analyzed using traditional methods. Therefore, it is crucial to develop real-time monitoring methods that can detect and prevent derailments, ensuring the safety of railway transportation.To address and prevent train derailments, this paper introduces an impact monitoring method focused on rail fasteners. This technique enables the rapid detection of single-wheel derailments from the track. By analyzing the behavior of rail fasteners under various load conditions, we have identified key parameters that can be utilized to detect potential derailment risks. The method primarily involves monitoring changes in lateral and longitudinal vibrational energy, along with the intervals between impacts on fasteners, and incorporating the vertical displacement of wheels to trigger a derailment alarm.Simulation and experimental results demonstrate that this approach can accurately identify derailment characteristics and issue timely warnings, effectively preventing and mitigating train derailments. This method offers a practical solution for enhancing rail transportation safety and contributes to the advancements in this field.

Numerical Simulation Study on the Hydrothermal Characteristics and Dynamic Response of the Embankment–Bridge Transition Zone in Cold Regions

The chain reaction of bridge abutment structure caused by frost heave of the embankment–bridge transition zone filler in cold regions has a great impact on the smoothness of railway lines, which will bring great challenges to the normal operation, safety, and maintenance of rail transit in cold regions under the action of long-term dynamic load. In this paper, the hydrothermal model and dynamic analysis model of the embankment–bridge transition zone are established, and the frost heave deformation rule and dynamic response characteristics of the embankment–bridge transition zone under frost heave conditions are studied. The results show that the effect of the bridge abutment structure on vertical frost heave is mainly concentrated in the range of the bridge abutment, and the vertical frost heave near the abutment is much smaller than other parts away from the abutment. The dynamic response and wheel–rail contact force of the embankment–bridge transition zone are significantly different under non-frost heave and frost heave conditions. Frost heave may cause a higher risk of derailment. This study provides a scientific reference for the design, construction, and safe operation and maintenance of embankment–bridge transition zones in cold regions, and has certain practical engineering significance.

Running safety control performance of high-speed trains on bridges under seismic excitation utilizing tuned mass damper

The safety of high-speed trains on bridges during seismic conditions is of paramount concern, especially for high-pier bridges characterized by lower lateral stiffness. The risk of train derailment during earthquakes can increase due to heightened low-frequency excitation. While Tuned Mass Dampers (TMDs) have proven effective in mitigating structural responses, their influence on time-varying vehicle-bridge interactions under earthquakes remains an unexplored area of study. In this research, a 1:10 scale model of a high-speed train-track-bridge coupling system, incorporating a nonlinear wheel-rail interface, was subjected to testing using a four-shaking-table system. This system exhibited good control accuracy and synchronization rates. The experimental results were used to validate the accuracy of the numerical model for the train-track-bridge coupled system under various train speeds. Subsequently, the seismic control performance of TMDs on high-speed trains was assessed through a combination of experimental tests and numerical simulations. Both sets of results, from the experimental and numerical approaches, confirmed the effectiveness of TMDs in controlling acceleration and force-related parameters for both moving and stationary trains. Notably, the control performance is most pronounced when vibrations closely align with the TMD's operating frequency. Additionally, this study delved into the mechanism of train vibration control and conducted a comprehensive parametric investigation, considering factors like pier heights (24 m–50 m), train speeds (0–300 km/h), ground motion intensities (0.04 g–0.21 g), and TMD mass ratios (0.03–0.08). The findings revealed that TMDs have a more significant impact on enhancing the safety index of trains for high-pier bridges characterized by lower frequencies. For instance, in the case of a 50 m pier, the running train's derailment coefficient can be reduced by 34.94 %. However, the control action is narrowband, effectively mitigating train vibrations near the bridge's natural frequency but less effective outside the working frequency range and absolute base acceleration.

Competency ambidexterity to achieve leadership excellence and reduce derailment risk in a globalized world: a cross-cultural study

Competency ambidexterity to achieve leadership excellence and reduce derailment risk in a globalized world: a cross-cultural study

The relationship between freight train length and the risk of derailment.

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.

Robust assessment of railway vehicle safety risks in operation using a proposed data-driven wheel profile generation approach: Design of computer experiments and surrogate models

Worldwide objectives for railway vehicles are increased capacity, faster travels and higher levels of safety. In the vehicle-track complex system, assessing and controlling the interactions between the wheels and the rail track is crucial to these goals. Wheel profiles are specifically designed to steer the vehicle and avoid derailment. Maintenance standards and train operating companies establish safe envelopes for wheel profile geometric parameters. A design of experiments is conducted to model relationships between allowable wheel parameters and expected vehicle safety risks, which is supported by condition monitoring data from operation. Such a robust assessment is missing in the literature. The applied methods consist of: (i) selection of predictors and pre-processing, based on literature, standards and a purely data-driven approach to generate wheel profiles; (ii) space-filling design, using Latin hypercube sampling; (iii) obtaining vehicle responses and post-processing, using a multibody dynamics commercial software and according to standards; (iv) surrogate modelling, using Gaussian processes and linear models; (v) sensitivity analysis, through Sobol indices; (vi) safety assessment, analysing response surfaces. Wheels with large flange height and thickness result in higher flange climb derailment risks. The proposed approach allows quantifying this risk as a function of profile parameters and mitigate it through maintenance actions.

Mechanism of cross-level settlements and void accumulation of wide and conventional sleepers in railway ballast

AbstractThe cross-level and twist irregularities are the most dangerous irregularity types that could cause wheel unloading with the risk of derailments and additional maintenance expenses. However, the mechanism of the irregularities initiation and development is unclear. The motivation of the present study was the previous experimental studies on the application of wide sleepers in the ballasted track. The long-term track geometry measurements with wide sleepers show an enormous reduction of the vertical longitudinal irregularities compared to the conventional track. However, wide sleepers had higher twist and cross-section level irregularities. The present paper aims to explain the phenomenon by discrete element method (DEM) modeling the development process of sleeper inhomogeneous support at cross-level depending on the sleeper form. The DEM simulations show that the maximal settlement intensity is up to 3.5 times lower for a wide sleeper in comparison with the conventional one. Nevertheless, the cross-level differential settlements are almost the same for both sleepers. The particle loading distribution after all loading cycles is concentrated on the smaller area, up to the half sleeper length, with fully unloaded zones under sleeper ends. Ballast flow limitation under the central part of the sleeper could improve the resilience of wide sleepers to the development of cross-level irregularities. The mechanism of initiation of the cross-level irregularity is proposed, which assumes the loss of sleeper support under sleeper ends. The further growth of inhomogeneous settlements along the sleeper is assumed as a result of the interaction of two processes: ballast flow due to dynamic impact during void closing and on the other side high pressure due to the concentration of the pressure under the middle part of the sleeper. The DEM simulation results support the assumption of the mechanism and agree with the experimental studies.

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.

Modelling and numerical simulation of high-speed railway slab track structure

In terms of maintenance and structural behavior, slab track proves to be an advantage over conventional ballasted track due to increasing train speed, axle load, and traffic density. Since the vibration, noise, and risk of derailment, all accelerate as train speed increases, an in-depth investigation of track dynamics becomes essential for identifying the fundamental cause of the problem. In this paper modelling and numerical simulation of high-speed railway slab track structure has been studied using finite element method. Using the multi-body simulation approach and the finite element method a model of the 3D slab track system is developed. The slab track model has rail, rail pad, and concrete slab, HBL, and subgrade layers. In order to determine the fundamental frequency and the mode shapes associated with it, a modal analysis is carried out. Dynamic response, or acceleration against frequency curves derived via harmonic response analysis, is the result of the numerical simulation. The dynamic reaction of the structure of a high-speed slab track is studied, and the effect of elastic materials on reducing vibration is investigated. The results suggest that a layer of elastic material, like a slab of mat, inserted between a layer of concrete slab and a layer of HBL is capable of lowering the amount of vibration response of the track.

A Review of Levitation Control Methods for Low- and Medium-Speed Maglev Systems

Maglev transportation is a highly promising form of transportation for the future, primarily due to its friction-free operation, exceptional comfort, and low risk of derailment. Unlike conventional transportation systems, maglev trains operate with no mechanical contact with the track. Maglev trains achieve levitation and guidance using electromagnetic forces controlled by a magnetic levitation control system. Therefore, the magnetic levitation control system is of utmost importance in maintaining the stable operation performance of a maglev train. However, due to the open-loop instability and strong nonlinearity of the control system, designing an active controller with self-adaptive ability poses a substantial challenge. Moreover, various uncertainties exist, including parameter variations and unknown external disturbances, under different operating conditions. Although several review papers on maglev levitation systems and control methods have been published over the last decade, there has been no comprehensive exploration of their modeling and related control technologies. Meanwhile, many review papers have become outdated and no longer reflect the current state-of-the-art research in the field. Therefore, this article aims to summarize the models and control technologies for maglev levitation systems following the preferred reporting items for systematic reviews and meta-analysis (PRISMA) criteria. The control technologies mainly include linear control methods, nonlinear control methods, and artificial intelligence methods. In addition, the article will discuss maglev control in other scenarios, such as vehicle–guideway vibration control and redundancy and fault-tolerant design. First, the widely used maglev levitation system modeling methods are reviewed, including the modeling assumptions. Second, the principle of the control methods and their control performance in maglev levitation systems are presented. Third, the maglev control methods in other scenarios are discussed. Finally, the key issues pertaining to the future direction of maglev levitation control are discussed.

Efficient DNA walker guided by ordered cruciform-shaped DNA track for ultrasensitive and rapid electrochemical detection of lead ion

The rational design of DNA tracks is an effective pathway to guide the autonomous movement and high-efficiency recognition in DNA walkers, showing outstanding advantages for the cascade signal amplification of electrochemical biosensors. However, the uncontrolled distance between two adjacent tracks on the electrode could increase the risk of derailment and interruption of the reaction. Hence, a novel four-way balanced cruciform-shaped DNA track (C-DNT) was designed as a structured pathway to improve the effectiveness and stability of the reaction in DNA walkers. In this work, two kinds of cruciform-shaped DNA were interconnected as a robust structure that could avoid the invalid movement of the designed DNA walker on the electrode. When hairpin H2 was introduced onto the electrode, the strand displacement reaction (SDR) effectively triggered movements of the DNA walker along the cruciform-shaped track while leaving ferrocene (Fc) on the electrode, leading to a significant enhancement of the electrochemical signal. This design enabled the walker to move in an excellent organized and controllable manner, thus enhancing the reaction speed and walking efficiency. Compared to other walkers moving on random tracks, the reaction time of the C-DNT-based DNA walker could be reduced to 20 min. Lead ion (Pb2+) was used as a model target to evaluate the analytical performance of this biosensor, which exhibited a low detection limit of 0.033 pM along with a wide detection ranging from 0.1 pM to 500 nM. This strategy presented a novel concept for designing a high-performance DNA walker-based sensing platform for the detection of contaminants.

Investigations on wagon–track interaction and running safety with unsupported sleepers

Unsupported sleeper defects are not rare for the ballasted track. Based on the status quo of the railway in Kosovo, this paper presents a study on the wagon–track interaction and running safety risk with unsupported sleepers. A three-dimensional wagon–track dynamic model is first developed and validated through a full-scale field experiment. The dynamic response features of wagon and track components are respectively presented and analysed under the sleeper hanging condition. Parameter studies and safety analysis are then conducted with different wagon speeds, including gap height, unsupported quantity, wagon load, and asymmetric effects of the unsupported sleeper. The results indicate that unsupported sleepers will induce wheel–rail impact and significantly exacerbate the vibrations of the wagon and track. The wavelength corresponding to the dominant frequency for the wagon vertical acceleration (ACC) is equal to the wheelbase. Moreover, adjacent ballasts of the unsupported zone exhibit maximal displacements and ACCs, which could be the compelling evidence to explain the extension of the unsupported zone. The derailment risk is typically higher when the unsupported sleepers are asymmetrically distributed compared to the scenarios with symmetrically unsupported sleepers. Additionally, the combined effects of unsupported sleepers and wheel flat will further deteriorate the wagon running safety. The presented results can provide a significant reference for the wagon speed increase and track maintenance in Kosovo and other countries with deficient railway infrastructure.

Postearthquake train operation safety assessment model based on machine learning

Abstract Assessing the seismic risk to high-speed rail systems with limited structural damage data is a challenging task. This study employs machine learning algorithms to predict the wheel–rail forces of high-speed trains operating under postearthquake conditions, particularly when infrastructure along the railway is damaged. By developing a postearthquake train operation safety assessment model, this article effectively predicts the impact of track irregularities induced by different earthquake intensities on wheel–rail interactions. The results obtained through feature selection and regression analysis using the Random Forest algorithm provide valuable insights into key safety indicators for postearthquake train operations. Compared to traditional multibody dynamic models, this approach significantly improves the efficiency of analysis and computation. An analysis of the results across multiple speed levels reveals that trains operating at 250 km/h face derailment risks when subjected to high-intensity earthquakes (PGA > 0.6 g). The proposed predictive safety assessment model demonstrates that adjusting train speeds according to seismic intensity can effectively enhance operational safety, offering critical support for postearthquake emergency recovery efforts.