An internal ballistic model of electromagnetic railgun based on PFN coupled with multi-physical field and experimental validation

To accelerate the practicality of electromagnetic railguns,it is necessary to use a combination of threedimensional numerical simulation and experiments to study the mechanism of bore damage.In this paper,a three-dimensional numerical model of the augmented railgun with four parallel unconventional rails is introduced to simulate the internal ballistic process and realize the multi-physics field coupling calculation of the rail gun,and a test experiment of a medium-caliber electromagnetic launcher powered by pulse formation network(PFN)is carried out.Various test methods such as spectrometer,fiber grating and high-speed camera are used to test several parameters such as muzzle initial velocity,transient magnetic field strength and stress-strain of rail.Combining the simulation results and experimental data,the damage condition of the contact surface is analyzed.

On the Polygonal Wear Evolution of Heavy-Haul Locomotive Wheels due to Wheel/Rail Flexibility and Its Mitigation Measures

Wheel polygonal wear can immensely worsen wheel/rail interactions and vibration performances of the train and track,and ultimately,lead to the shortening of service life of railway components.At present,wheel/rail medium-or high-frequency frictional interactions are perceived as an essential reason of the high-order polygonal wear of railway wheels,which are potentially resulted by the flexible deformations of the train/track system or other external excitations.In this work,the effect of wheel/rail flexibility on polygonal wear evolution of heavy-haul locomotive wheels is explored with aid of the long-term wheel polygonal wear evolution simulations,in which different flexible modeling of the heavy-haul wheel/rail coupled system is implemented.Further,the mitigation measures for the polygonal wear of heavy-haul locomotive wheels are discussed.The results point out that the evolution of polygonal wear of heavy-haul locomotive wheels can be veritably simulated with consideration of the flexible effect of both wheelset and rails.Execution of mixed-line operation of heavy-haul trains and application of multicut wheel re-profiling can effectively reduce the development of wheel polygonal wear.This research can provide a deep-going understanding of polygonal wear evolution mechanism of heavy-haul locomotive wheels and its mitigation measures.

KL-SG High-Speed Rail-a catalyst for national economic development Sri Viknesh Permalu and Karthigesu Nagarajoo

Purpose-In an increasingly interconnected world,transportation infrastructure has emerged as a critical determinant of economic growth and global competitiveness.High-speed rail(HSR),characterized by its exceptional speed and efficiency,has garnered widespread attention as a transformative mode of transportation that transcends borders and fosters economic development.The Kuala Lumpur-Singapore(KL-SG)HSR project stands as a prominent exemplar of this paradigm,symbolizing the potential of HSR to serve as a catalyst for national economic advancement.Design/methodologylapproach-This paper is prepared to provide an insight into the benefits and advantages of HSR based on proven case studies and references from global HSRs,including China,Spain,France and Japan.Findings-The findings that have been obtained focus on enhanced connectivity and accessibility,attracting foreign direct investment,revitalizing regional economies,urban development and city regeneration,boosting tourism and cultural exchange,human capital development,regionai integration and environmental and sustainability benefits.Originality/value-The KL-SG HSR,linking Kuala Lumpur and Singapore,epitomizes the potential for HSR to be a transformative agent in the realm of economic development.This project encapsulates the aspirations of two dynamic Southeast Asian economies,united in their pursuit of sustainable growth,enhanced connectivity and global competitiveness.By scrutinizing the KLSG High-Speed Rail through the lens of economic benchmarking,a deeper understanding emerges of how such projects can drive progress in areas such as cross-border trade,tourism,urban development and technological innovation.

Effect of deformation parameters on the austenite dynamic recrystallization behavior of a eutectoid pearlite rail steel

Understandings of the effect of hot deformation parameters close to the practical production line on grain refinement are crucial for enhancing both the strength and toughness of future rail steels.In this work,the austenite dynamic recrystallization(DRX)behaviors of a eutectoid pearlite rail steel were studied using a thermo-mechanical simulator with hot deformation parameters frequently employed in rail production lines.The single-pass hot deformation results reveal that the prior austenite grain sizes(PAGSs)for samples with different deformation reductions decrease initially with an increase in deformation temperature.However,once the deformation temperature is beyond a certain threshold,the PAGSs start to increase.It can be attributed to the rise in DRX volume fraction and the increase of DRX grain with deformation temperature,respectively.Three-pass hot deformation results show that the accumulated strain generated in the first and second deformation passes can increase the extent of DRX.In the case of complete DRX,PAGS is predominantly determined by the deformation temperature of the final pass.It suggests a strategic approach during industrial production where part of the deformation reduction in low temperature range can be shifted to the medium temperature range to release rolling mill loads.

Corrosion Test of the Steel Plate in a WJ-8 Fastener for High Speed Rail

It was found that the steel plate in the composite plate in the WJ-8 fastener used in high speed rail is rusty. The objective of this study is to test the zinc coating of the steel plate. A literature review was conducted to identify the zinc coating techniques, and the companies that can provide different coating service was identified. A salt fog chamber was built that was in compliance with the ANSI B117 code, and the steel plates that were coated by the identified companies were tested using the salt fog chamber. The results indicated that the coating technique that had the best performance in preventing corrosion was the Greenkote plates with passivation. The galvanized option had the roughest coating layer, and it was the most reactive in the salt water solution. This makes it non-ideal for the dynamic rail environment because the increased friction of the plate could damage the supports, especially during extreme temperatures that would cause the rail to expand or contract. Greenkote with Phosphate and ArmorGalv also provided increased corrosion prevention with a smooth, strong finish, but it had more rust on the surface area than the Greenkote with ELU passivation. The ArmorGalv sample had more rust on the surface area than the Greenkote samples. This may not be a weakness in the ArmorGalv process;rather, it likely was the result of this particular sample not having the added protection of a colored coating.

Human intrusion detection for high-speed railway perimeter under all-weather condition

Purpose – The paper aims to solve the problem of personnel intrusion identification within the limits of highspeed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy ofobject recognition in dark and harsh weather conditions.Design/methodology/approach – This paper adopts the fusion strategy of radar and camera linkage toachieve focus amplification of long-distance targets and solves the problem of low illumination by laser lightfilling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm formulti-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposesa linkage and tracking fusion strategy to output the correct alarm results.Findings – Simulated intrusion tests show that the proposed method can effectively detect human intrusionwithin 0–200 m during the day and night in sunny weather and can achieve more than 80% recognitionaccuracy for extreme severe weather conditions.Originality/value – (1) The authors propose a personnel intrusion monitoring scheme based on the fusion ofmillimeter wave radar and camera, achieving all-weather intrusion monitoring;(2) The authors propose a newmulti-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring underadverse weather conditions;(3) The authors have conducted a large number of innovative simulationexperiments to verify the effectiveness of the method proposed in this article.

Optimal Scheduling of Multiple Rail Cranes in Rail Stations with Interference Crane Areas

In this paper,we consider a multi-crane scheduling problem in rail stations because their operations directly influence the throughput of the rail stations.In particular,the job is not only assigned to cranes but also the job sequencing is implemented for each crane to minimize the makespan of cranes.A dual cycle of cranes is used to minimize the number of working cycles of cranes.The rail crane scheduling problems in this study are based on the movement of containers.We consider not only the gantry moves,but also the trolley moves as well as the rehandle cases are also included.A mathematical model of multi-crane scheduling is developed.The traditional and parallel simulated annealing(SA)are adapted to determine the optimal scheduling solutions.Numerical examples are conducted to evaluate the applicability of the proposed algorithms.Verification of the proposed parallel SA is done by comparing it to existing previous works.Results of numerical computation highlighted that the parallel SA algorithm outperformed the SA and gave better solutions than other considered algorithms.

Determining future high speed rail review topics through bibliometric analysis

As High Speed Rail(HSR)has proliferated globally,so has a related research field dedicated to exploring and addressing its unique issues.Yet,studies to understand and classify the HSR research domain are limited.This paper addresses the gap,using bibliometric analysis to identify future research areas and 20 candidate topics for literature review based on keyword analysis through VOSviewer.Article and review papers related to HSR published in the last 20 years(2003-2022)were retrieved from Scopus,and then analyzed to determine the split in knowledge between languages,the collaboration between countries and institutions,highly productive and cited journals,and research topics which have and have not been reviewed.Approximately 30%of the search results were published exclusively in Chinese,highlighting the importance of extending the evaluation to cover both languages.This is a novel aspect of the work,which has enabled the recognition of potential knowledge gaps.It is recommended that future reviews incorporate works in both languages,possibly through international collaboration.Institutions in China and other countries that are strong collaborators have been identified,as well as relevant,highly cited journals.

A critical review of wheel/rail high frequency vibration-induced vibration fatigue of railway bogie in China

Purpose–This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.Design/methodology/approach–Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators.Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration.This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration,including a brief introduction of short-pitch irregularities,associated high frequency vibration in railway bogie,typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.Findings–The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms.The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components.The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure,and the fatigue crack usually initiates from the defect of the weld seam.Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities.The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment,and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.Originality/value–The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

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

Purpose – Straightness measurement of rail weld joint is of essential importance to railway maintenance. Dueto the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a5-m wavelength range, leaving a significant knowledge gap in this field.Design/methodology/approach – In this study, the authors used the well-established inertial referencemethod (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methodshave been applied in different types of rail straightness measurement trollies, respectively. These instrumentswere tested in a high-speed rail section within a certain region of China. The test results were ultimatelyvalidated through using traditional straightedge and feeler gauge methods as reference data to evaluate the railweld joint straightness within the 5-m wavelength range.Findings – The research reveals that IR-method and MCR-method produce reasonably similar measurementresults for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy forwavelengths 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/value – The research compare two methods’ measurement effects in a longer wavelength rangeand demonstrate the superiority of MCR-method.

Effect of Spray Rails on Takeoff Performance of Amphibian Aircraft

Amphibian aircraft have seen a rise in popularity in the recreational and utility sectors due to their ability to take off and land on both land and water, thus serving a myriad of purposes, such as aerobatics, surveillance, and firefighting. Such seaplanes must be aerodynamically and hydrodynamically efficient, particularly during the takeoff phase. Naval architects have long employed innovative techniques to optimize the performance of marine vessels, including incorporating spray rails on hulls. This research paper is dedicated to a comprehensive investigation into the potential utilization of spray rails to enhance the takeoff performance of amphibian aircraft. Several spray rail configurations obtained from naval research were simulated on a bare Seamax M22 amphibian hull to observe an approximate 10% - 25% decrease in water resistance at high speeds alongside a 3% reduction in the takeoff time. This study serves as a motivation to improve the design of the reference airplane hull and a platform for detailed investigations in the future to improve modern amphibian design.

Smart City Rail Transit Operation and Management Information Construction Strategy

Rail transit is considered one of the safest and most efficient modes of transportation.Ticketing,vehicle dispatching,and passenger flow control during rail transit operations in China have been improving over the years.Smart city construction and intelligent management models has also been increasingly emphasized with the rapid development of information and internet technology.Therefore,it is essential to conduct relevant research and discussions to improve the overall efficiency and quality of urban rail transit operation and management.This article provides an overview of smart city rail transit operation and management informatization,the principles of construction,and the functions of smart city rail transit operation and management informatization.Additionally,it discusses the strategies for the construction of smart city rail transit operation and management information and its development prospects.

Shift2Rail创新制动系统

为匹配高性能无线传输技术在轨道列车上的使用,实现制动系统的虚拟验证和认证,对传统制动系统进行功能细化分解,定义适用于线控制动的设计需求并对部分功能进行整合和相关安全性分析,以此开发出一套高SIL等级的电子控制单元;同时基于对轮轨不同黏着实测数据的收集,对恢复黏着系统进行性能需求分析,介绍实验室黏着建模过程及仿真模型,开发出一套防滑自适应算法并配合撒砂装置以满足低黏着条件下制动力的有效施加;另外对新型摩擦副进行匹配研发,开发电机械制动设备和长寿命低磨耗的制动盘、制动闸片以及无摩擦低噪音的涡流制动系统。最后对制动系统的评估和验证流程进行分析,提出对其进行虚拟验证和认证的流程和方法。

Contact Mechanism of Rail Grinding with Open-Structured Abrasive Belt Based on Pressure Grinding Plate

The current research of abrasive belt grinding rail mainly focuses on the contact mechanism and structural design.Compared with the closed structure abrasive belt grinding,open-structured abrasive belt grinding has excellent performance in dynamic stability,consistency of grinding quality,extension of grinding mileage and improvement of working efficiency.However,in the contact structure design,the open-structured abrasive belt grinding rail using a profiling pressure grinding plate and the closed structure abrasive belt using the contact wheel are different,and the contact mechanisms of the two are different.In this paper,based on the conformal contact and Hertz theory,the contact mechanism of the pressure grinding plate,abrasive belt and rail is analyzed.Through finite element simulation and static pressure experiment,the contact behavior of pressure grinding plate,abrasive belt and rail under single concentrated force,uniform force and multiple concentrated force was studied,and the distribution characteristics of contact stress on rail surface were observed.The results show that under the same external load,there are three contact areas under the three loading modes.The outer contour of the middle contact area is rectangular,and the inner contour is elliptical.In the contact area at both ends,the stress is extremely small under a single concentrated force,the internal stress is drop-shaped under a uniform force,and the internal stress under multiple concentration forces is elliptical.Compared with the three,the maximum stress is the smallest and the stress distribution is more uniform under multiple concentrated forces.Therefore,the multiple concentrated forces is the best grinding pressure loading mode.The research provides support for the application of rail grinding with open-structured abrasive belt based on pressure grinding plate,such as contact mechanism and grinding pressure mode selection.

Rail fastener detection of heavy railway based on deep learning

Image detection based on machine learning and deep learning currently has a good application prospect for railway fault diagnosis,with good performance in feature extraction and the accuracy of image localization and good classification results.To improve the speed of locating small target objects of fasteners,the YOLOv5 framework model with faster algorithm speed is selected.To improve the classification accuracy of fasteners,YOLOv5-based heavy-duty railway rail fastener detection is proposed.The anchor size is modified on the original basis to improve the attention to small targets of fasteners.The CBAM(Convolutional Block Attention Module)module and TPH(Transformer Prediction Head)module are introduced to improve the speed and accuracy issues.The rail fasteners are divided into 6 categories.Experiment comparisons show that before the improvement,the MAP@0.5 value of all categories are close to the peak of 0.989 after the epoch of 150,and the F1 score approaches 1 with confidence in the interval(0.2,0.95).The improved mAP@0.5 value approached the highest value of 0.991 after the epoch of 75,and the F1 score approached 1 with confidence in the interval(0.01,0.95).The experiment results indicate that the improved YOLOv5 model proposed in this paper is more suitable for the task of detecting rail fasteners.

Embedded System Development for Detection of Railway Track Surface Deformation Using Contour Feature Algorithm

Derailment of trains is not unusual all around the world,especially in developing countries,due to unidentified track or rolling stock faults that cause massive casualties each year.For this purpose,a proper condition monitoring system is essential to avoid accidents and heavy losses.Generally,the detection and classification of railway track surface faults in real-time requires massive computational processing and memory resources and is prone to a noisy environment.Therefore,in this paper,we present the development of a novel embedded system prototype for condition monitoring of railway track.The proposed prototype system works in real-time by acquiring railway track surface images and performing two tasks a)detect deformation(i.e.,faults)like squats,shelling,and spalling using the contour feature algorithm and b)the vibration signature on that faulty spot by synchronizing acceleration and image data.A new illumination scheme is also proposed to avoid the sunlight reflection that badly affects the image acquisition process.The contour detection algorithm is applied here to detect the uneven shapes and discontinuities in the geometrical structure of the railway track surface,which ultimately detects unhealthy regions.It works by converting Red,Green,and Blue(RGB)images into binary images,which distinguishes the unhealthy regions by making them white color while the healthy regions in black color.We have used the multiprocessing technique to overcome the massive processing and memory issues.This embedded system is developed on Raspberry Pi by interfacing a vision camera,an accelerometer,a proximity sensor,and a Global Positioning System(GPS)sensors(i.e.,multi-sensors).The developed embedded system prototype is tested in real-time onsite by installing it on a Railway Inspection Trolley(RIT),which runs at an average speed of 15 km/h.The functional verification of the proposed system is done successfully by detecting and recording the various railway track surface faults.An unhealthy frame’s onsite detection processing time was recorded at approximately 25.6ms.The proposed system can synchronize the acceleration data on specific railway track deformation.The proposed novel embedded system may be beneficial for detecting faults to overcome the conventional manual railway track condition monitoring,which is still being practiced in various developing or underdeveloped countries.

Effects of Rare-earth and Microalloying Elements on the Microstructure Characteristics of Hypereutectoid Rails

We performed thermal simulation experiments of double-pass deformation of hypereutectoid rails with different microalloying elements at a cooling rate of 1℃/s and deformation of 80%to explore the influence of rare-earth and microalloying elements on the structure of hypereutectoid rails and optimize the composition design of hypereutectoid rails.Scanning electron microscopy,transmission electron microscopy,X-ray diffraction,and other characterization techniques were employed to quantitatively analyzed the effects of different microalloying elements,including rare-earth elements,on pearlite lamellar spacing,cementite characteristics,and dislocation density.It was found that the lamellar spacing was reduced by adding various microalloying elements.Cementite lamellar thickness decreased with the refinement of pearlite lamellar spacing while the cementite content per unit volume increased.Local cementite spheroidization,dispersed in the ferrite matrix in granular form and thus playing the role of dispersion strengthening,was observed upon adding cerium(Ce).The contributions of dislocation density to the alloy strength of four steel sheet samples with and without the addition of nickel,Ce,and Ce–copper(Cu)composite were 26,27,32,and 37 MPa,respectively,indicating that the Ce–Cu composite had the highest dislocation strengthening effect.The Ce–Cu composite has played a meaningful role in the cementite characteristics and dislocation strengthening,which provides a theoretical basis for optimizing the composition design of hypereutectoid rails in actual production conditions.

Rail Surface Defect Detection Based on Improved UPerNet and Connected Component Analysis

To guarantee the safety of railway operations,the swift detection of rail surface defects becomes imperative.Traditional methods of manual inspection and conventional nondestructive testing prove inefficient,especially when scaling to extensive railway networks.Moreover,the unpredictable and intricate nature of defect edge shapes further complicates detection efforts.Addressing these challenges,this paper introduces an enhanced Unified Perceptual Parsing for Scene Understanding Network(UPerNet)tailored for rail surface defect detection.Notably,the Swin Transformer Tiny version(Swin-T)network,underpinned by the Transformer architecture,is employed for adept feature extraction.This approach capitalizes on the global information present in the image and sidesteps the issue of inductive preference.The model’s efficiency is further amplified by the windowbased self-attention,which minimizes the model’s parameter count.We implement the cross-GPU synchronized batch normalization(SyncBN)for gradient optimization and integrate the Lovász-hinge loss function to leverage pixel dependency relationships.Experimental evaluations underscore the efficacy of our improved UPerNet,with results demonstrating Pixel Accuracy(PA)scores of 91.39%and 93.35%,Intersection over Union(IoU)values of 83.69%and 87.58%,Dice Coefficients of 91.12%and 93.38%,and Precision metrics of 90.85%and 93.41%across two distinct datasets.An increment in detection accuracy was discernible.For further practical applicability,we deploy semantic segmentation of rail surface defects,leveraging connected component processing techniques to distinguish varied defects within the same frame.By computing the actual defect length and area,our deep learning methodology presents results that offer intuitive insights for railway maintenance professionals.

Rail Internal Defect Detection Method Based on Enhanced Network Structure and Module Design Using Ultrasonic Images

Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe operation of high-speed trains.For this reason,a rail internal defect detection method based on an enhanced network structure and module design using ultrasonic images is proposed in this paper.First,a data augmentation method was used to extend the existing image dataset to obtain appropriate image samples.Second,an enhanced network structure was designed to make full use of the high-level and low-level feature information in the image,which improved the accuracy of defect detection.Subsequently,to optimize the detection performance of the proposed model,the Mish activation function was used to design the block module of the feature extraction network.Finally,the pro-posed rail defect detection model was trained.The experimental results showed that the precision rate and F1score of the proposed method were as high as 98%,while the model’s recall rate reached 99%.Specifically,good detec-tion results were achieved for different types of defects,which provides a reference for the engineering application of internal defect detection.Experimental results verified the effectiveness of the proposed method.

Cascading Delays for the High-Speed Rail Network Under Different Emergencies:A Double Layer Network Approach

High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.