Mechanical Properties of Railway High-strength Manufactured Sand Concrete: Typical Lithology, Stone Powder Content and Strength Grade

In order to achieve the large-scale application of manufactured sand in railway high-strength concrete structure,a series of high-strength manufactured sand concrete(HMC)are prepared by taking the manufactured sand lithology(tuff,limestone,basalt,granite),stone powder content(0,5%,10%,15%)and concrete strength grade(C60,C80,C100)as variables.The evolution of mechanical properties of HMC and the correlation between cubic compressive strength and other mechanical properties are studied.Compared to river sand,manufactured sand enhances the cubic compressive strength,axial compressive strength and elastic modulus of concrete,while its potential microcracks weaken the flexural strength and splitting tensile strength of concrete.Stone powder content displays both positive and negative effects on mechanical properties of HMC,and the stone powder content is suggested to be less than 10%.The empirical formulas between cubic compressive strength and other mechanical properties are proposed.

Seismic isolation design and resilience improvement of railway station considering the influence of near-fault pulse-like ground motions

To improve the resilience of railway stations,a typical station was selected as the research object,and an isolation design was introduced.Twenty-four groups of near-fault pulse-like ground motions were selected.The seismic resilience of the no-isolation railway stations(NIRS)and the isolation railway stations(IRS)were compared to provide a numerical result of the improvement in resilience.The results show that in the station isolation design,the station's functional requirements and structural characteristics should be considered and the appropriate placement of isolation bearings is under the waiting room.Under the action of a rare earthquake,the repair cost,repair time,rate of harm and death of the IRS were decreased by 8.04 million,18.30 days,6.93×10^(-3)and 1.21×10^(-3),respectively,when compared to the NIRS.The IRS received a seismic resilience grade of three-stars and the NIRS only one-star,indicating that rational isolation design improves the seismic resilience of stations.Thus,for the design of stations close to earthquake faults,it is suggested to utilize appropriate isolation techniques to improve their seismic resilience.

Historical Changes and Future Projections of Extreme Temperature and Precipitation along the Sichuan-Tibet Railway

Based on multiresource high-resolution in situ and satellite merged observations along with model simulations from the Coordinated Regional Climate Downscaling Experiment(CORDEX),this study first investigated historical changes in extreme temperature and precipitation during the period of 1979-2018 in areas along the Sichuan-Tibet Railway,and then projected the future changes in the frequency and intensity of extreme temperature and precipitation under the RCP(Representative Concentration Pathway)4.5 and 8.5 scenarios.This paper is expected to enhance our understanding of the spatiotemporal variability in the extreme temperature and precipitation along the Sichuan-Tibet Railway,and to provide scientific basis to advance the Sichuan-Tibet Railway construction and operation.The results show that temperatures in the Sichuan-Tibet region display a noticeable warming trend in the past 40 years,and the increase of minimum temperature is significantly higher than that of maximum temperature in the northwest of the region.Significant increase of precipitation is found mainly over the northwest of the Tibetan Plateau.Except for Lhasa and its surrounding areas,precipitation over other areas along the Sichuan-Tibet Railway shows no significant change in the past 40 years,as indicated in five datasets;however,precipitation along the railway has shown a remarkable decrease in the past 20 years in the TRMM satellite dataset.The warm days and nights have clearly increased by 6 and 5 day decade1-for 1979-2019,while cold days and nights have markedly decreased by about 6.6 and 3.6 day decade-1,respectively.In the past 20 years,the areas with increased precipitation from very wet days and extremely wet days are mainly distributed to the north of the Sichuan-Tibet Railway,while in the areas along the railway itself,the very wet days and extremely wet days are decreasing.Under RCPs 4.5 and 8.5,the temperature in the Sichuan-Tibet region will increase significantly,and the frequency of extreme high(low)temperature events in the late 21 st century(2070-2099)will greatly increase(decrease)by about 50%-80%(10%)compared with occurrences in the late 20 th century(1970-1999).Meanwhile,the frequency of very wet days and extremely wet days in the Sichuan-Tibet region will increase by about 2%-19% and 2%-5%,respectively,and the areas along the Sichuan-Tibet Railway will be affected by more extreme high temperature and extreme precipitation events.

Reliability guarantee framework for the Sichuan-Tibet Railway

The Sichuan-Tibet Railway is facing extraordinary challenges in terms of construction,operation,and maintenance because of its extremely complicated natural environment and geological conditions.Consequently,countermeasures are necessary and urgent to ensure its safety and reliability in the whole life cycle.This study proposes a novel reliability framework to guarantee the ideal operation state of the Sichuan-Tibet Railway.Reliability application in many fields are summarized,including military equipment,rail locomotive,and railway engineering.Given the fact that the Sichuan-Tibet Railway is a complex giant system,Nine-Connotation was summarized(i.e.,safety,inherent reliability,testability,maintainability,supportability,environmental adaptability,predictability,resilience,and durability)under the goal of optimizing the operational efficiency.On the basis of the concept of the Nine-Connotation and the understanding of reliability transmission mechanism,the framework of reliability for the Sichuan-Tibet Railway was established,which can facilitate a comprehensive and real-time evaluation of all situations with a clear hierarchy.The proposed framework is composed of a resilience management system,an integrated technology system,and a dynamic reliability assessment system.The pathway for its application on railway construction was developed in this study.The proposed framework can assist in well-informed decisions for the construction,as well as the operation of the Sichuan-Tibet Railway.On the basis of a top-down design concept for the first time,this study emphasizes the railway's availability and validity to complete the assigned tasks as a whole,that is,operational efficiency.It also shows the reliability transmission and control mechanism of the railway's giant complex system,innovating and establishing the management principle of great safety and great reliability over the life cycle.

The Influence of Sichuan-Tibet Railway on the Accessibility and Economic Development of City Propers along the Line: Taking Chengdu and Ya’an as Examples

The Chengdu-Ya’an section of Sichuan-Tibet Railway(STR),which has already started operation,is taken as an example.First,we apply the weighted average travel time and gravity model to analyze the accessibility of the site cities and the economic link intensity among them,with visualization by ArcGIS.Then,we use the difference-in-differences model with panel data of three cities from 2018 to 2019 to test the impact of the Chengdu-Ya’an section on regional urbanization along the route.The results show that the opening of the Chengdu-Ya’an section has significantly improved the accessibility and economic link of areas along the line and promoted regional economic development and urbanization.It is expected that the opening of the entire line of STR will have more significant impacts,which requires continuous research and attention in the future.

Analysis of the future trends of typical mountain glacier movements along the Sichuan-Tibet Railway based on ConvGRU network

The anomalous movements of glaciers cause disasters,such as debrisflows and landslides.It is very important to assess the glacier movements and their future trends.Glacier velocity refers to movement process.The current research aims to analyse past and current spatiotemporal changes in glacier velocity.No study has used neural network model to conduct a spatiotemporal prediction for glacier velocity.Therefore,this paper selected typical mountain glaciers G2 and G5 along the Sichuan-Tibet Railway as research objects and constructed the Convolutional Gate Recurrent Unit(ConvGRU)spatiotemporal prediction model based on 1988–2018 Landsat data to predict velocities in 2019–2028,and analysed the future trends of G2 and G5.The evaluation indexes met the model requirements to a large extent,quantitatively showing that the model has high accuracy and can successfully capture thefluctuation changes in time series data of glacier velocity.The mean deviations of G2 and G5 were 0.09 and-0.47 m/yr,respectively,reflecting the high reliability of the model applied to extraction of glacier velocity.The velocities of G2 and G5 showed a slow downtrend withfluctuations;that is,they will not cause damage to the construction and operation of the Sichuan-Tibet Railway in the short term.

Traction power systems for electrified railways:evolution,state of the art,and future trends

Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.

Deformation monitoring of long-span railway bridges based on SBAS-InSAR technology

The deformation monitoring of long-span railway bridges is significant to ensure the safety of human life and property.The interferometric synthetic aperture radar(In SAR)technology has the advantage of high accuracy in bridge deformation monitoring.This study monitored the deformation of the Ganjiang Super Bridge based on the small baseline subsets(SBAS)In SAR technology and Sentinel-1A data.We analyzed the deformation results combined with bridge structure,temperature,and riverbed sediment scouring.The results are as follows:(1)The Ganjiang Super Bridge area is stable overall,with deformation rates ranging from-15.6 mm/yr to 10.7 mm/yr(2)The settlement of the Ganjiang Super Bridge deck gradually increases from the bridge tower toward the main span,which conforms to the typical deformation pattern of a cable-stayed bridge.(3)The sediment scouring from the riverbed cause the serious settlement on the bridge’s east side compared with that on the west side.(4)The bridge deformation negatively correlates with temperature,with a faster settlement at a higher temperature and a slow rebound trend at a lower temperature.The study findings can provide scientific data support for the health monitoring of long-span railway bridges.

A review of artificial intelligence applications in high-speed railway systems

In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.

High-speed railway track components inspection framework based on YOLOv8 with high-performance model deployment

Railway inspection poses significant challenges due to the extensive use of various components in vast railway networks,especially in the case of high-speed railways.These networks demand high maintenance but offer only limited inspection windows.In response,this study focuses on developing a high-performance rail inspection system tailored for high-speed railways and railroads with constrained inspection timeframes.This system leverages the latest artificial intelligence advancements,incorporating YOLOv8 for detection.Our research introduces an efficient model inference pipeline based on a producer-consumer model,effectively utilizing parallel processing and concurrent computing to enhance performance.The deployment of this pipeline,implemented using C++,TensorRT,float16 quantization,and oneTBB,represents a significant departure from traditional sequential processing methods.The results are remarkable,showcasing a substantial increase in processing speed:from 38.93 Frames Per Second(FPS)to 281.06 FPS on a desktop system equipped with an Nvidia RTX A6000 GPU and from 19.50 FPS to 200.26 FPS on the Nvidia Jetson AGX Orin edge computing platform.This proposed framework has the potential to meet the real-time inspection requirements of high-speed railways.

Dynamic response of mountain tunnel,bridge,and embankment along the Sichuan-Tibet transportation corridor to active fault based on model tests

The Sichuan-Tibet transportation corridor is prone to numerous active faults and frequent strong earthquakes.While extensive studies have individually explored the effect of active faults and strong earthquakes on different engineering structures,their combined effect remains unclear.This research employed multiple physical model tests to investigate the dynamic response of various engineering structures,including tunnels,bridges,and embankments,under the simultaneous influence of cumulative earthquakes and stick-slip misalignment of an active fault.The prototype selected for this study was the Kanding No.2 tunnel,which crosses the Yunongxi fault zone within the Sichuan-Tibet transportation corridor.The results demonstrated that the tunnel,bridge,and embankment exhibited amplification in response to the input seismic wave,with the amplification effect gradually decreasing as the input peak ground acceleration(PGA)increased.The PGAs of different engineering structures were weakened by the fault rupture zone.Nevertheless,the misalignment of the active fault may decrease the overall stiffness of the engineering structure,leading to more severe damage,with a small contribution from seismic vibration.Additionally,the seismic vibration effect might be enlarged with the height of the engineering structure,and the tunnel is supposed to have a smaller PGA and lower dynamic earth pressure compared to bridges and embankments in strong earthquake zones crossing active faults.The findings contribute valuable insights for evaluating the dynamic response of various engineering structures crossing an active fault and provide an experimental reference for secure engineering design in the challenging conditions of the Sichuan-Tibet transportation corridor.

A discussion about the limitations of the Eurocode’s high-speed load model for railway bridges

High-speed railway bridges are subjected to normative limitations concerning maximum permissible deck accelerations.For the design of these structures,the European norm EN 1991-2 introduces the high-speed load model(HSLM)—a set of point loads intended to include the effects of existing high-speed trains.Yet,the evolution of current trains and the recent development of new load models motivate a discussion regarding the limits of validity of the HSLM.For this study,a large number of randomly generated load models of articulated,conventional,and regular trains are tested and compared with the envelope of HSLM effects.For each type of train,two sets of 100,000 load models are considered:one abiding by the limits of the EN 1991-2 and another considering wider limits.This comparison is achieved using both a bridge-independent metric(train signatures)and dynamic analyses on a case study bridge(the Canelas bridge of the Portuguese Railway Network).For the latter,a methodology to decrease the computational cost of moving loads analysis is introduced.Results show that some theoretical load models constructed within the stipulated limits of the norm can lead to effects not covered by the HSLM.This is especially noted in conventional trains,where there is a relation with larger distances between centres of adjacent vehicle bogies.

Research on digital twin technology and its application in intelligent operation and maintenance of highspeed railway infrastructure

Purpose–This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.Design/methodology/approach–This paper provides a comprehensive overview of the definition,connotations,characteristics and key technologies of digital twin technology.It also conducts a thorough analysis of the current state of digital twin applications,with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure.Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study,the paper details the construction process of the twin system from the perspectives of system architecture,theoretical definition,model construction and platform design.Findings–Digital twin technology can play an important role in the whole life cycle management,fault prediction and condition monitoring in the field of high-speed rail operation and maintenance.Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.Originality/value–This paper systematically summarizes the main components of digital twin railway.The general framework of the digital twin bridge is given,and its application in the field of intelligent operation and maintenance is prospected.

Unraveling engineering disturbance effects on deformation in red-bed mudstone railway cuttings:incorporating crack-facilitated moisture diffusion

Red-bed mudstone, prevalent in southwest China, poses a formidable challenge due to its hydrophilic clay minerals, resulting in expansion, deformation, and cracking upon exposure to moisture. This study addresses uplift deformation disasters in high-speed railways by employing a moisture diffusion-deformation-fracture coupling model based on the finite-discrete element method(FDEM). The model integrates the influence of cracks on moisture diffusion. The investigation into various excavation depths reveals a direct correlation between depth and the formation of tensile cracks at the bottom of the railway cutting. These cracks expedite moisture migration, significantly impacting the temporal and spatial evolution of the moisture field. Additionally, crack expansion dominates hygroscopic deformation, with the lateral coordinate of the crack zone determining peak vertical displacement. Furthermore, key factors influencing deformation in railway cuttings, including the swelling factor and initial moisture content at the bottom of the cutting, are explored. The number of tensile and shear cracks increases with greater excavation depth, particularly concerning shear cracks. Higher swelling factors and initial moisture contents result in an increased total number of cracks, predominantly shear cracks. Numerical calculations provide valuable insights, offering a scientific foundation and directional guidance for the precise prevention, control, prediction, and comprehensive treatment of mudstone-related issues in high-speed railways.

Formation and ecological response of sand patches in the protection system of Shapotou section of the Baotou-Lanzhou railway,China

The development of bare patches typically signifies a process of ecosystem degradation.Within the protection system of Shapotou section of the Baotou-Lanzhou railway,the extensive emergence of bare sand patches poses a threat to both stability and sustainability.However,there is limited knowledge regarding the morphology,dynamic changes,and ecological responses associated with these sand patches.Therefore,we analyzed the formation and development process of sand patches within the protection system and its effects on herbaceous vegetation growth and soil nutrients through field observation,survey,and indoor analysis methods.The results showed that sand patch development can be divided into three stages,i.e.,formation,expansion,and stabilization,which correspond to the initial,actively developing,and semi-fixed sand patches,respectively.The average dimensions of all sand patch erosional areas were found to be 7.72 m in length,3.91 m in width,and 0.32 m in depth.The actively developing sand patches were the largest,and the initial sand patches were the smallest.Throughout the stage of formation and expansion,the herbaceous community composition changed,and the plant density decreased by more than 50.95%.Moreover,the coverage and height of herbaceous plants decreased in the erosional area and slightly increased in the depositional lobe;and the fine particles and nutrients of soils in the erosional area and depositional lobe showed a decreasing trend.In the stabilization phases of sand patches,the area from the inlet to the bottom of sand patches becomes initially covered with crusts.Vegetation and 0-2 cm surface soil condition improved in the erosional area,but this improvement was not yet evident in the depositional lobe.Factors such as disturbance,climate change,and surface resistance to erosion exert notable influences on the formation and dynamics of sand patches.The results can provide evidence for the future treatment of sand patches and the management of the protection system of Shapotou section of the Baotou-Lanzhou railway.

A Railway Fastener Inspection Method Based on Abnormal Sample Generation

Regular fastener detection is necessary to ensure the safety of railways.However,the number of abnormal fasteners is significantly lower than the number of normal fasteners in real railways.Existing supervised inspectionmethods have insufficient detection ability in cases of imbalanced samples.To solve this problem,we propose an approach based on deep convolutional neural networks(DCNNs),which consists of three stages:fastener localization,abnormal fastener sample generation based on saliency detection,and fastener state inspection.First,a lightweight YOLOv5s is designed to achieve fast and precise localization of fastener regions.Then,the foreground clip region of a fastener image is extracted by the designed fastener saliency detection network(F-SDNet),combined with data augmentation to generate a large number of abnormal fastener samples and balance the number of abnormal and normal samples.Finally,a fastener inspection model called Fastener ResNet-8 is constructed by being trained with the augmented fastener dataset.Results show the effectiveness of our proposed method in solving the problem of sample imbalance in fastener detection.Qualitative and quantitative comparisons show that the proposed F-SDNet outperforms other state-of-the-art methods in clip region extraction,reaching MAE and max F-measure of 0.0215 and 0.9635,respectively.In addition,the FPS of the fastener state inspection model reached 86.2,and the average accuracy reached 98.7%on 614 augmented fastener test sets and 99.9%on 7505 real fastener datasets.

Privacy-Preserving Large-Scale AI Models for Intelligent Railway Transportation Systems:Hierarchical Poisoning Attacks and Defenses in Federated Learning

The development of Intelligent Railway Transportation Systems necessitates incorporating privacy-preserving mechanisms into AI models to protect sensitive information and enhance system efficiency.Federated learning offers a promising solution by allowing multiple clients to train models collaboratively without sharing private data.However,despite its privacy benefits,federated learning systems are vulnerable to poisoning attacks,where adversaries alter local model parameters on compromised clients and send malicious updates to the server,potentially compromising the global model’s accuracy.In this study,we introduce PMM(Perturbation coefficient Multiplied by Maximum value),a new poisoning attack method that perturbs model updates layer by layer,demonstrating the threat of poisoning attacks faced by federated learning.Extensive experiments across three distinct datasets have demonstrated PMM’s ability to significantly reduce the global model’s accuracy.Additionally,we propose an effective defense method,namely CLBL(Cluster Layer By Layer).Experiment results on three datasets have confirmed CLBL’s effectiveness.

Influence of pier height on the safety of trains running on high-speed railway bridges during earthquakes

Sudden earthquakes pose a threat to the running safety of trains on high-speed railway bridges,and the stiffness of piers is one of the factors affecting the dynamic response of train-track-bridge system.In this paper,a experiment of a train running on a high-speed railway bridge is performed based on a dynamic experiment system,and the corresponding numerical model is established.The reliability of the numerical model is verified by experiments.Then,the experiment and numerical data are analyzed to reveal the pier height effects on the running safety of trains on bridges.The results show that when the pier height changes,the frequency of the bridge below the 30 m pier height changes greater;the increase of pier height causes the transverse fundamental frequency of the bridge close to that of the train,and the shaking angle and lateral displacement of the train are the largest for bridge with 50 m pier,which increases the risk of derailment;with the pier height increases from 8 m to 50 m,the derailment coefficient obtained by numerical simulations increases by 75% on average,and the spectral intensity obtained by experiments increases by 120% on average,two indicators exhibit logarithmic variation.

Research on the path of effective management of participation in joint-venture railway companies by China railway group

Purpose-Following the regional restructuring,the number of joint-venture railway companies in which the Group participates has significantly increased.This paper aims to explore the challenges faced by China Railway Group in managing participation in joint-venture railway companies.The study seeks to propose specific approaches to ensure the effective management of these companies,thereby maximizing the benefits of the regional restructuring and supporting the development of a strong transportation country and a modern infrastructure system.Design/methodology/approach-Based on the change in the shareholding relationship between China Railway Group and the joint-venture railway companies,and considering the current situation of the regional restructuring of these companies,as well as the insights from existing literature and typical case studies,this paper proposes some specific paths for effective management of joint-stock railway companies which China Railway Group participated in.Findings-The problems in participation management are the unclear dual leadership role of the party committee,the lack of discourse power,the lack of synergy between shareholders,the increasing risk of sustainable operation of the loss-making companies and the role of dispatched personnel is not fully played.Based on the theories,combined with the existing research and practical cases,the paper proposed specific approaches,such as perfecting top-level system design,maintaining the discourse power,carrying out differentiated management,arranging personnel rationally,arranging shareholders synergy,and innovating methods to provide references for China Railway Group’s subsequent management of joint venture railway companies.Originality/value-This paper contributes to the existing literature by providing a comprehensive analysis of the challenges faced by China Railway Group in managing participation in joint-venture railway companies following the regional restructuring.The study offers novel insights and practical recommendations for addressing these challenges.The findings can serve as valuable references for China Railway Group’s subsequent management of joint-venture railway companies which participated in,as well as for other stateowned enterprises facing similar challenges in managing their joint ventures.

Fault Diagnosis Scheme for Railway Switch Machine Using Multi-Sensor Fusion Tensor Machine

Railway switch machine is essential for maintaining the safety and punctuality of train operations.A data-driven fault diagnosis scheme for railway switch machine using tensor machine and multi-representation monitoring data is developed herein.Unlike existing methods,this approach takes into account the spatial information of the time series monitoring data,aligning with the domain expertise of on-site manual monitoring.Besides,a multi-sensor fusion tensor machine is designed to improve single signal data’s limitations in insufficient information.First,one-dimensional signal data is preprocessed and transformed into two-dimensional images.Afterward,the fusion feature tensor is created by utilizing the images of the three-phase current and employing the CANDE-COMP/PARAFAC(CP)decomposition method.Then,the tensor learning-based model is built using the extracted fusion feature tensor.The developed fault diagnosis scheme is valid with the field three-phase current dataset.The experiment indicates an enhanced performance of the developed fault diagnosis scheme over the current approach,particularly in terms of recall,precision,and F1-score.