Rail Section Research Articles

Determination of the dynamic stiffness matrix of a rail damper and application to vibration decay rate

In this paper, the 6×6 dynamic stiffness matrix of a rail damper seen by a short section of rail is defined based on the force simplification theory, and a method to determine the matrix is presented. According to the method, frequency response functions (FRFs) between specific points on the rail as a rigid body are measured with hammer testing. These FRFs are then used to express the acceleration of the mass center of the rail as well as the rail's angular acceleration. As the third step, the equations of motion of the rail are established based on the laws of momentum and moment of momentum, from which the dynamic stiffness matrix can be worked out. The method is then applied to determine the dynamic stiffnesses of a typical damper, and the determined dynamic striffnesses are combined with an infinite periodic track model to stduy the effect of the damper on the verical and lateral vibration decay rates of the rail.

The Wheel–Rail Contact Force for a Heavy-Load Train Can Be Measured Using a Collaborative Calibration Algorithm

The wheel–rail contact force is a crucial indicator for ensuring the secure operation of a heavy-load train. However, obtaining the real-time wheel–rail contact force of a heavy-load train is a challenging task as, due to safety considerations, it is not possible to install instrumented wheelsets on heavy-load trains. This work presents a novel approach to quantify the wheel–rail contact force of a heavy-load train, utilizing a cooperative calibration methodology. First, a ground measurement platform for the wheel–rail contact force of a heavy-load train is constructed on a selected rail section. The railway inspection car’s wheel–rail contact force measurement system is fine-tuned using a multilayer perceptron calibration approach, and the ground platform then uses the results to fine-tune the railway inspection car’s examined wheelset. Second, based on actual measured data on the wheel–rail contact force of a heavy-load train, and using the golden jackal optimization algorithm, the multilayer perceptron correction approach is employed to create a data relationship mapping model. This model correlates the corrected data on the wheel–rail contact force obtained from the railway inspection car with the wheel–rail contact force of a heavy-haul train with an axle load of 25 tons, and the precision of the mapping is guaranteed. Finally, by combining the wheel–rail contact force correction method for the railway inspection car and the contact force mapping model between the railway inspection car and the heavy-load train, collaborative calibration of the wheel–rail contact force of the heavy-load train is realized. The experimental results under two working conditions show that this method can realize high-precision, real-time measurement of the wheel–rail contact force of a heavy-load train. For the working condition of a straight-line section, the calibration error was within 1.593 kN, and the MAPE was 0.105%; for the working condition of a curved-line section, the calibration error was 2.344 kN, and the RMSE was 184.72 N.

An efficient 3D finite element procedure for simulating wheel–rail cyclic contact and ratcheting

Various models for simulating rail ratcheting behaviour were developed to study rolling contact fatigue (RCF) damage in rails. However, limitations remain in terms of the accuracy of wheel–rail contact modelling and computational efficiency of the cyclic loading simulation. This study developed an efficient 3D finite element (FE) procedure to simulate ratcheting in rails subjected to numerous load cycles. The procedure simulates a wheel rolling repeatedly over a rail section with updated stress–strain states, enabling automatically executed cyclic loading simulation given a predefined number of cycles. To ensure the accuracy of the contact modelling, the effect of meshing schemes on subsurface stress distribution was examined. In addition, the FE contact model with the selected meshing scheme, which balances accuracy and computational efficiency, was verified against the widely accepted CONTACT program. Subsequently, a non-linear kinematic hardening (NLKH) steel material was used in the FE model for ratcheting simulations with up to 100 wheel-loading cycles. The rail surface and subsurface stress states were replicated under partial-slip wheel–rail rolling contact conditions with traction coefficients of 0.10, 0.20 and 0.35, respectively. The ratcheting behaviour was extensively analysed in terms of plastic deformation, contact patch evolution, and ratcheting rates. The simulated plastic deformation was found to alter the contact geometry and thus contact stresses, which in turn affect further accumulation of plastic deformation and subsequent ratcheting strains. These findings highlighted the importance of considering the interplay between the rail ratcheting behaviour of the rail and evolving contact conditions for predicting ratcheting and RCF damage in rails.

Study on monitoring broken rails of heavy haul railway based on ultrasonic guided wave

Real-time monitoring of broken rails in heavy haul railways is crucial for ensuring the safe operation of railway lines. U78CrV steel is a common material used for heavy haul line rails in China. In this study, the semi-analytical finite element (SAFE) method is employed to calculate the dispersion curves and modal shapes of ultrasonic guided waves in U78CrV heavy steel rails. Guided wave modes that are suitable for detecting rail cracks across the entire cross-section are selected based on the total energy of each mode and the vibration energy in the rail head, web, and foot. The excitation method for the chosen mode is determined by analyzing the energy distribution of the mode shape on the rail surface. The ultrasonic guided wave (UGW) signal in the rail is analyzed using ANSYS three-dimensional finite element simulation. The group velocity of the primary mode in the guided wave signal is obtained through continuous wavelet transform to confirm the existence of the selected mode. It is validated that the selected mode can be excited by examining the similarity between the vibration shapes of a specific rail section and all modal vibration shapes obtained through SAFE. Through simulation and field verification, the guided wave mode selected and excited in this study demonstrates good sensitivity to cracks at the rail head, web, and foot, and it can propagate over distances exceeding 1 km in the rail. By detecting the reflected signal of the selected mode or the degree of attenuation of the transmitted wave, long-distance monitoring of broken rails in heavy-haul railway tracks can be achieved.

THERMAL BUCKLING ON CURVED AND TANGENT RAILWAYS: PARAMETRIC STUDY

AbstractThis study investigates the thermal buckling in railway infrastructures, which can cause derailments and safety risks. The research analyses the influence of various parameters on thermal buckling, focusing on misalignment and ballast resistance. Using a finite element model, curved and tangent tracks are simulated, considering rail sections, sleeper materials, fastener stiffness and initial imperfections. Results demonstrate that ballast resistance is the most critical factor, with compacted ballast increasing buckling temperatures by up to 127%. Additionally, rail imperfections significantly impact temperature increases. A new design guide is proposed for operating conditions under different conditions.

Acoustic emission-based assessment of weld effects on the health monitoring of the rail section: an experimental study

Railways are a vital lifeline for both passengers and freight, with an extensive network connected by robust welded joints. This study explores the potential of Acoustic Emission (AE) techniques in rail health monitoring, particularly in the context of rail sections and their relationship with welds. While AE-based health monitoring has gained attention, a significant gap exists in understanding welds’ influence. This research bridges this gap by examining the interplay between welds and health monitoring. Welds introduce complexities in AE wave propagation, crucial for precise health assessments. Through artificial AE source simulation using the Pencil Lead Break (PLB) method across diverse rail segments, specialized sensors capture AE signals. Rigorous analysis, involving signal processing and statistical methods, reveals how welds impact AE wave behaviour and health assessment accuracy. Importantly, this research underscores how welds alter AE wave propagation, ensuring accurate health evaluations. This study’s insights hold far-reaching implications, not only for enhancing current rail system maintenance but also for advancing our understanding of the critical interrelationship between welds and health monitoring, thus contributing to the longevity and reliability of rail systems.

Experimental and numerical investigation into the characteristics of continuously measured rail profiles and its influence on simulations of vehicle-track interaction

This study investigates the influence of variations in rail profiles along the operation direction on simulations of vehicle-track interaction by combining numerical and experimental approaches. For this purpose, a procedure for the evaluation of rail profile measurement data is proposed based on the GEKON 3D inspection instrument. By establishing a dynamic vehicle-track interaction model, a comparative evaluation is performed with the uniform rail profiles or variations in the rail profiles. The results indicate that the proposed procedure can process raw data from continuous measurements, and the indices in terms of rail section loss, curvature index, and wheel-rail contact geometry can be evaluated. Furthermore, the influence of the rail profile variations along the train operating direction should not be overlooked, especially in curved tracks where the symmetry of the left and right rail profiles is poor. By considering the influence of variations in rail profiles, the simulated results are more likely to reflect the actual situation of dynamic vehicle-track interaction. It is believed that the use of uniform rail profiles may result in accuracy loss when analyzing dynamic vehicle responses, especially under scenarios of long-distance wheel-rail contact status.

Comparison study on measurement of rail weld joint between inertial reference method and multi-point chord reference method

PurposeStraightness measurement of rail weld joint is of essential importance to railway maintenance. Due to the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a 5-m wavelength range, leaving a significant knowledge gap in this field.Design/methodology/approachIn this study, the authors used the well-established inertial reference method (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methods have been applied in different types of rail straightness measurement trollies, respectively. These instruments were tested in a high-speed rail section within a certain region of China. The test results were ultimately validated through using traditional straightedge and feeler gauge methods as reference data to evaluate the rail weld joint straightness within the 5-m wavelength range.FindingsThe research reveals that IR-method and MCR-method produce reasonably similar measurement results for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy for wavelengths exceeding 3 m. Furthermore, it was observed that IR-method, while operating at a slower speed, carries the risk of derailing and is incapable of detecting rail weld joints and low joints within the track.Originality/valueThe research compare two methods’ measurement effects in a longer wavelength range and demonstrate the superiority of MCR-method.

Rail Flaw Imaging Prototype Based on Improved Ultrasonic Synthetic Aperture Focus Method

This paper presents an experimental prototype developed for rail flaw imaging. This capability can help obtain quantitative information on detected flaws during manual flaw verification. Ultrasonic synthetic aperture focus (SAF) imaging has advantages over phased-array imaging for both speed and accuracy. The prototype developed is hosted in a portable and battery-powered carry-on size case. The probe is a linear ultrasonic array mounted on a wedge and with a position encoder to build 3D point clouds from 2D beamformed images. The prototype includes several advances over the basic SAF technique, including sparse subarray firing that allows fast imaging speeds (e.g., 25 Hz) without sacrificing image accuracy. Validation results are presented from scans performed on rail sections from the FRA rail defect library, which contains natural transverse defects and artificial end-drilled hole defects. The tests showed good accuracy in defect size and shape, as compared to the available ground truth information, for defects located away from the railhead corners. Additional developments are required to properly cover the head corners, and especially in the case of heavily worn rails.

Birefringence Technique for Evaluating Thermal Stresses in Railroad Rails

This paper discusses the development of an in situ noncontact electromagnetic acoustic transducer (EMAT) nondestructive evaluation technology to determine rail neutral temperature and estimate rail stress in continuous welded rail (CWR). Stresses develop in CWR due to a lack of expansion joints to accommodate thermal expansion and contraction of the rail when ambient temperatures vary over time. The novelty of the work presented is the usage of ultrasonic birefringence properties using EMATs to estimate thermally induced stresses in rails. EMATs produce polarized shear waves propagating through the rail web in the pulse-echo mode. Experimental tests were performed on machined 136RE and 141RE rail material with applied compressive and tensile stresses to explore the stress-birefringence behavior. Two additional sets of experimental tests were conducted on full-size rail sections with in situ surface conditions to study variations in the in situ birefringence and the acoustic stress constant in different rail materials including 115RE rail, 119RE rail, two different 136RE rails, and 141RE rail. The results show a highly linear relationship between the stresses applied and the measured acoustic birefringence.

Understanding the behaviour of magnetic field distribution of railgun under transient conditions using finite element method

The magnetic field distribution in the rails is a crucial factor in comprehending railgun behaviour. The projectile's rapid movement has a significant impact on the magnetic field. If the dispersion of the magnetic field conclusions regarding the conductors are known suitable methods can be used to sketch the magnetic field distribution. The railgun operates on the premise that a high current flow through the rails and armature will create a strong magnetic field. As a result, before designing magnetic shielding, it is necessary to study the features of the magnetic field distribution. The shape of rail and armature cross section is very essential in rail gun design as it determines the magnetic field distribution over rail and armature. The rail gun geometries with rectangular, convex and concave rail cross-sections are compared and simulated using finite element method (FEM). This method is used to determine the magnetic field distribution over rail and armature by sweeping armature position for different rail cross sections. It is observed that for the different rail/armature shapes like rectangular, convex and concave shapes, the C shaped convex armature possesses strong magnetic fields with minimum current density concentration at the throat and trailing end of the armature. From simulation, it can be shown that the magnetic flux density is a descending function of the central angle. The electromagnetic (EM) rail gun launching mechanism was therefore proven to be compatible with the circular concave armature.

A full 3D reconstruction of rail tracks using a camera array

This research addresses limitations found in existing 3D track reconstruction studies, which often focus solely on specific rail sections or encounter deployment challenges with rolling stock. To address this challenge, we propose an innovative solution: a rolling-stock embedded arch camera array scanning system. The system includes a semi-circumferential focusing vision array, an arch camera holder, and a Computer Numerical Control machine to simulate track traverse. We propose an optimal configuration that balances accuracy, full rail coverage, and modelling efficiency. Sensitivity analysis demonstrates a reconstruction accuracy within 0.4 mm when compared to Lidar-generated ground truth models. Two real-world experiments validate the system's effectiveness following essential data preprocessing. This integrated technique, when combined with rail rolling stocks and robotic maintenance platforms, facilitates swift, unmanned, and highly accurate track reconstruction and surveying.

Transformers à Grande Vitesse: Massively parallel real-time predictions of train delay propagation

Robust travel time predictions are of prime importance in managing any transportation infrastructure, and particularly in rail networks where they have major impacts both on traffic regulation and passenger satisfaction. We aim at predicting the travel time of trains on rail sections at the scale of an entire rail network in real-time, by estimating trains’ delays relative to a theoretical circulation plan.Predicting the evolution of a given train’s delay is a uniquely hard problem, distinct from mainstream road traffic forecasting problems, since it involves several hard-to-model phenomena: train spacing, station congestion and heterogeneous rolling stock among others. We first offer empirical evidence of the previously unexplored phenomenon of delay propagation at the scale of a railway network, leading to delays being amplified by interactions between trains and the network’s physical limitations.We then contribute a novel technique using the transformer architecture and pre-trained embeddings to make real-time massively parallel predictions for train delays at the scale of the whole rail network (over 3000 trains at peak hours, making predictions at an average horizon of 70 min). Our approach yields very positive results on real-world data when compared to currently-used and experimental prediction techniques.

Analytical and numerical study of hot rolling railway rail sections with the help of simulation and finite element software

Hot rolling of sections is one of the metal forming processes used to shape materials into profiles with a fixed cross-section, such as road rails. Iron is chosen for this process due to its repeatability. Despite the numerous equipment and high costs associated with it, the analysis of this process and its simulation can be highly desirable. In this process, the initial raw piece is passed through several rollers until the desired section's shape is created (1,2). The more passes are made, the greater the reduction in the cross-sectional area, and the tolerances increase. During rail rolling, several key factors play a crucial role, including the length of the workpiece, cross-section change, piece deviation, roller speed, and friction. This article focuses on investigating the effective parameters in this process using simulation software. For the rolling analysis, we use an isothermal and rigid model of rollers, considering the heat transfer between the rollers and the rail during the shaping process. The analysis is performed using thermal stress solutions in Abaqus/explicit. Additionally, the workpiece may deviate due to the asymmetry of the top and bottom shapes. Hence, we examine the effects of the friction coefficient between the part and the rollers on rail deflection, stress values, strain, and rolling force. The results indicate that the maximum stress on the rail's surface occurs below the points of contact with the rollers, leading to a higher percentage reduction.

Assessing the Influence of Welded Joint on Health Monitoring of Rail Sections: An Experimental Study Employing SVM and ANN Models

Assessing the Influence of Welded Joint on Health Monitoring of Rail Sections: An Experimental Study Employing SVM and ANN Models

Effect of different gaps in the conductor rail joints on the current-carrying wear performance of carbon skateboards/conductive rail contact

The interconnection of the conductive rail for intercity trains involves multiple sections of steel rails. The presence of gaps in the joints between these steel rails greatly impacts the efficacy of current transmission in collector–conductor rail systems. A total of nine joints with different inclined angles and widths were devised to investigate the influencing characteristics of gaps on the current–carrying friction of carbon skateboards/conductive rail contact. The nine joints were tested by using a pin-disc current–carrying friction tester to evaluate the wear performance of different contact pairs. The findings indicated that the presence of gaps in conductor rail joints resulted in a decrease in the coefficient of friction, but an increase in the electrical contact resistance. Furthermore, these gaps substantially impacted the wear rate of carbon skateboards. Specifically, when the gap width was 1.5 mm, the influence of the inclined angle of the gaps on the electrical contact resistance diminished. Additionally, the gap characterized by a width of 0.5 mm and an inclined angle of 90° exhibited a comparatively reduced influence on the wear performance of the contact pairs.

Eigenvalue-based approach for buckling analysis of metre gauge railway tracks incorporating train load effects

Railway track buckling is a significant concern that can jeopardise train operations and passenger safety. This paper presents a comprehensive buckling analysis of railway tracks using Eigenvalue-based simplified approach in the finite element method, while considering the influence of passing trains. The study focuses on evaluating the buckling behaviour of the track, taking into account dynamic response and the interaction between the train and track. The finite element model encompasses the track structure, including rails, sleepers, ballast, and fasteners, and incorporates material properties, geometrical constraints, and boundary conditions. Through eigenvalue analysis, critical buckling modes and corresponding buckling loads are determined, providing insights into the track's stability under different loading scenarios. Furthermore, a parametric study is conducted to investigate the effects of various factors such as unconstrained length, lateral resistance and rail sections on the buckling behaviour. This study enhances the understanding of buckling phenomena in railway tracks and offers valuable information for track design, maintenance, and safety considerations. The findings contribute to improving the resilience and reliability of railway track systems, ultimately ensuring safe and efficient train operations.

A Review on the Development of a Track Irregularity Measurement Tool

Railway transportation is one of the most vital transportation modes for people and goods. Ensuring railway transportation safety and efficiency is very important. The condition of the track is one of the most vital factors in ensuring railway safety, as irregularities in the track can lead to severe accidents. Thus, it is essential to have proper gauges and methods to measure track irregularities. This paper will discuss different methods to measure track irregularities and their advantages and limitations. Several track irregularity measurement tools will be divided into groups based on different aspects, such as the contact types and their location. Contact methods can measure more detailed irregularities, but have limitations such as injury and equipment damage. Non-contact methods are less invasive and can measure larger rail sections, but are less accurate. The inspection method will be chosen based on the track configuration that must be carefully studied to ensure the most efficient and effective inspection methods for a rail type. Regardless of the method, it is important to keep developing and improving existing track irregularity measurement tools to increase efficiency and reduce measurement errors.

Lightweight design of automotive front rail based on topology optimisation and collision analysis

On the premise of meeting the crash performance, in order to reduce the weight of the front rail of the automotive and improve the level of lightweight of the vehicle.Combining with the goal of ‘carbon reduction‘, a method of topology optimisation was used to optimise the lightweight performance of automotive front rail.Topology optimisation takes the front rail of the automobile as the research object, the installation area of the front rail as the design space of topology optimisation, the minimum strain energy as the optimisation goal, the relative density of the grid of each element as the design variable, and the mass fraction of the front rail as a constraint to design the topology optimisation. Then the optimal material distribution of the front rail of the vehicle is obtained. On this basis, the geometric dimensions of the section of the front rail are multi-objective optimised, the sample data are designed and the response surface model of optimisation objective are established through the design of the Latin square experiment. Based on the NSGA-II algorithm, the optimised mathematical model is solved by multi-objective optimisation. The results show that the weight of the optimised structure is reduced by 6.5% compared with the original structure, and the collision absorption energy is improved, and the peak acceleration is significantly reduced.

Damage Localization in Rail Section Using Single AE Sensor Data: An Experimental Investigation with Deep Learning Approach

ABSTRACT Railways serve as a vital link for global trade and transportation in any country, but the rail sections are susceptible to damage due to factors such as traffic, extreme environment, and other unavoidable conditions. Monitoring such damages in real time is crucial to prevent casualties and economic losses. Non-destructive testing (NDT) techniques have been used for damage localization, and the acoustic emission (AE) technique has gained attention for real-time monitoring. However, conventional AE approaches are complex, time-consuming, and require multiple sensors. An alternative method is needed for easy and effective implementation of damage localization in rail sections using AE signals. In this study presents, a deep learning approach deploying Artificial Neural Network (ANN) and Support Vector Machine (SVM) models under AI is illustrated experimentally for easy and effective implementation of the damage localization process in the rail section. The novelty in this approach is the application of single AE sensor data which makes the damage localization process economical and less time-consuming. These findings have significant implications for the scientific community and rail transportation industries, ensuring safe and efficient operations..