Investigations into rail corrugation within metro systems have traditionally focused on specific mechanisms,thereby limiting the generalizability of proposed theories.Understanding the commonalities in rail corrugatio...Investigations into rail corrugation within metro systems have traditionally focused on specific mechanisms,thereby limiting the generalizability of proposed theories.Understanding the commonalities in rail corrugation across diverse metro lines remains pivotal for elucidating its underlying mechanisms.The present study conducted extensive field surveys and tracking tests across 14 Chinese metro lines.By employing t-distributed stochastic neighbor embedding(t-SNE)for dimensional reduction and employing the unsupervised clustering algorithm DBSCAN,the research redefines the classification of metro rail corrugation based on characteristic information.The analysis encompassed spatial distribution and temporal evolution of this phenomenon.Findings revealed that floating slab tracks exhibited the highest proportion of rail corrugation at 47%.Notably,ordinary monolithic bed tracks employing damping fasteners were more prone to inducing rail corrugation.Corrugation primarily manifested in curve sections with radii between 300 and 500 m,featuring ordinary monolithic bed track and steel-spring floating slab track structures,with wavelengths typically between 30 and 120 mm.Stick–slip vibrations of the wheel–rail system maybe led to short-wavelength corrugations(40–60 mm),while longer wavelengths(200–300 mm)exhibited distinct fatigue damage characteristics,mainly observed in steel-spring floating slab tracks and small-radius curve sections of ordinary monolithic bed tracks and ladder sleeper tracks.A classification system comprising 57 correlated features categorized metro rail corrugation into four distinct types.These research outcomes serve as critical benchmarks for validating various theories pertaining to rail corrugation formation.展开更多
The China comprehensive inspection train(CIT)is designed for evaluating railway infrastructure to ensure safe railway operations.The CIT integrates an array of inspection devices,capable of simultaneously assessing ra...The China comprehensive inspection train(CIT)is designed for evaluating railway infrastructure to ensure safe railway operations.The CIT integrates an array of inspection devices,capable of simultaneously assessing railway health condition parameters.The CIT450,representing the second generation,can reach a top speed of 450 km/h with inspection on the infrastructure.This paper begins by outlining the global evolution of inspection trains.It then focuses on the critical technologies underlying the CIT450,which include:(1)real-time inspection data acquisition with spatial and temporal synchronization;(2)intelligent fusion and centralized management of multi-source inspection data,enabling remote supervision of the inspection process;(3)technologies in inspecting track,train–track interaction,catenary,signalling systems,and train operating environment;and(4)AI-driven analysis and correlation of inspection data.The future developmental directions for comprehensive inspection trains are discussed finally.The CIT450’s approach to real-time railway health monitoring can enrich traditional inspection means,operational,and maintenance methods by enhancing inspection efficiency and automating railway maintenance.展开更多
The Third International Conference on Rail Transportation(ICRT),which was initiated by Southwest Jiaotong University and hosted by Tongji University,took place successfully in Shanghai,China,from August 7 to 9,2024.As...The Third International Conference on Rail Transportation(ICRT),which was initiated by Southwest Jiaotong University and hosted by Tongji University,took place successfully in Shanghai,China,from August 7 to 9,2024.As the chairman of the ICRT conference,I am delighted to witness its remarkable achievement.Based on the success of previous editions held in Chengdu in 2017 and 2021,this conference aims to provide a premier platform for extensive interaction and collaboration among universities,research institutions,and enterprises worldwide.展开更多
Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions mu...Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions must be carefully considered throughout their life cycle.Recent advancements in science and technology have enabled more effective structural monitoring of railway systems,largely driven by the adoption of intelligent strategies for inspection,maintenance,monitoring,and risk management.Research continues to expand and deepen the knowledge in this area;however,it remains a challenging field due to factors such as the complexity of railway systems,the high cost of implementation,and the need for reliable long-term data.展开更多
Replacing the energy density and convenience of diesel fuel for all forms of fossil fuel-powered trains presents significant challenges.Unlike the traditional evolutions of rail which has largely self-optimised to dif...Replacing the energy density and convenience of diesel fuel for all forms of fossil fuel-powered trains presents significant challenges.Unlike the traditional evolutions of rail which has largely self-optimised to different fuels and cost structures over 150 years,the challenges now present with a timeline of just a few decades.Fortunately,unlike the mid-1800s,simulation and modelling tools are now quite advanced and a full range of scenarios of operations and train trips can be simulated before new traction systems are designed.Full trip simulations of large heavy haul trains or high speed passenger trains are routinely completed controlled by emulations of human drivers or automated control systems providing controls of the“virtual train”.Recent developments in digital twins can be used to develop flexible and dynamic models of passenger and freight rail systems to support the new complexities of decarbonisation efforts.Interactions between many different traction components and the train multibody system can be considered as a system of systems.Adopting this multi-modelling paradigm enables the secure and integrated interfacing of diverse models.This paper demonstrates the application of the multi-modelling approach to develop digital twins for rail decarbonisation traction and it presents physics-based multi-models that include key components required for studying rail decarbonisation problems.Specifically,the challenge of evaluating zero-emission options is addressed by adding further layers of modelling to the existing fully detailed multibody dynamics simulations.The additional layers detail control options,energy storage,the alternate traction system components and energy management systems.These traction system components may include both electrical system and inertia dynamics models to accurately represent the driveline and control systems.This paper presents case study examples of full trip scenarios of both long haul freight trains and higher speed passenger trains.These results demonstrate the many complex scenarios that are difficult to anticipate.Flowing on from this,risks can be assessed and practical designs of zero-emission systems can be proposed along with the required recharging or refuelling systems.展开更多
Predictive maintenance is essential for the implementation of an innovative and efficient structural health monitoring strategy.Models capable of accurately interpreting new data automatically collected by suitably pl...Predictive maintenance is essential for the implementation of an innovative and efficient structural health monitoring strategy.Models capable of accurately interpreting new data automatically collected by suitably placed sensors to assess the state of the infrastructure represent a fundamental step,particularly for the railway sector,whose safe and continuous operation plays a strategic role in the well-being and development of nations.In this scenario,the benefits of a digital twin of a bonded insu-lated rail joint(IRJ)with the predictive capabilities of advanced classification algorithms based on artificial intelligence have been explored.The digital model provides an accurate mechanical response of the infrastructure as a pair of wheels passes over the joint.As bolt preload conditions vary,four structural health classes were identified for the joint.Two parameters,i.e.gap value and vertical displacement,which are strongly correlated with bolt preload,are used in different combinations to train and test five predictive classifiers.Their classification effectiveness was assessed using several performance indica-tors.Finally,we compared the IRJ condition predictions of two trained classifiers with the available data,confirming their high accuracy.The approach presented provides an interesting solution for future predictive tools in SHM especially in the case of complex systems such as railways where the vehicle-infrastructure interaction is complex and always time varying.展开更多
Supervised learning classification has arisen as a powerful tool to perform data-driven fault diagnosis in dynamical systems,achieving astonishing results.This approach assumes the availability of extensive,diverse an...Supervised learning classification has arisen as a powerful tool to perform data-driven fault diagnosis in dynamical systems,achieving astonishing results.This approach assumes the availability of extensive,diverse and labeled data corpora for train-ing.However,in some applications it may be difficult or not feasible to obtain a large and balanced dataset including enough representative instances of the fault behaviors of interest.This fact leads to the issues of data scarcity and class imbalance,greatly affecting the performance of supervised learning classifiers.Datasets from railway systems are usually both,scarce and imbalanced,turning supervised learning-based fault diagnosis into a highly challenging task.This article addresses time-series data augmentation for fault diagnosis purposes and presents two application cases in the context of railway track.The case studies employ generative adversarial networks(GAN)schemes to produce realistic synthetic samples of geometrical and structural track defects.The goal is to generate samples that enhance fault diagnosis performance;therefore,major attention was paid not only in the generation process,but also in the synthesis quality assessment,to guarantee the suitability of the samples for training of supervised learning classification models.In the first application,a convolutional classifier achieved a test accuracy of 87.5%for the train on synthetic,test on real(TSTR)scenario,while,in the second application,a fully-connected classifier achieved 96.18%in test accuracy for TSTR.The results indicate that the proposed augmentation approach produces samples having equivalent statistical characteristics and leading to a similar classification behavior as real data.展开更多
The integration of a large number of power electronic converters,such as railway power conditioner(RPC),introduces a series of problems,including harmonic interaction,stability issues,and wideband resonance,into the r...The integration of a large number of power electronic converters,such as railway power conditioner(RPC),introduces a series of problems,including harmonic interaction,stability issues,and wideband resonance,into the railway power supply system.To address these challenges,this paper proposes a novel harmonic resonance prevention measure for RPC-network-train interaction system.Firstly,a harmonic model,a parallel resonance impedance model,a series resonance admittance model,and a control stability model are each established for the RPC-network-train interaction system.Secondly,a comprehensive resonance impact factor(CRIF)is proposed to efficiently and accurately identify the key components affecting resonance,and to provide the selection results of optimization parameters for resonance prevention.Next,the initially selected parameters are constrained by the requirements of ripple current,reactive power and stability.Subsequently,the impedance parameters(control parameters and filter parameters)of the RPC are optimized with the objective of reshaping the parallel resonance impedance and series resonance admittance of the RPC-network-train interaction system,ensuring the output current har-monics of RPC meet standards to achieve resonance prevention,while ensuring the stable operation of the RPC.Finally,the proposed resonance prevention measure is verified under both light load and heavy load conditions using a simulation platform and a hardware-in-the-loop experimental platform.展开更多
The operational and regional conditions to which the prestressed concrete sleeper(PCS)is subjected in a railway track significantly contribute to its performance and durability.Maintaining the health of PCS poses chal...The operational and regional conditions to which the prestressed concrete sleeper(PCS)is subjected in a railway track significantly contribute to its performance and durability.Maintaining the health of PCS poses challenges,and one of these issues involves the potential occurrence of longitudinal cracks in reinforcing bars,which can be caused by various constructional,functional,and environmental factors.Longitudinal cracks in PCS compromise the structural performance,resulting in a reduced capacity to withstand the loads exerted by moving vehicles.The current evaluations not only fail to yield a precise parameter for estimating the behavior and response of the PCS,but they also overlook the specific conditions of the PCS,such as prestressing,and only provide limited information regarding existing damage.Balancing the need for accurate evaluation with consideration of costs and resources,and making informed decisions about maintenance and track performance enhancement,has become a multifaceted challenge in ensuring a robust PCS assessment.This research introduces a novel methodology to improve the evaluation of mechanical and geometrical parameters of PCS over their operational lifespan.The objective is to enhance the accuracy of PCS performance estimation by concentrating on detecting longitudinal cracks.The suggested approach seamlessly integrates model updating methods and the finite element(FE)approach to achieve an accurate and timely assessment of PCS conditions.This comprehensive examination scrutinizes the methodology by applying artificial cracks to the PCS.In addition to introducing this assessment approach,a detailed examination is conducted on a laboratory-simulated PCS featuring various combinations of longitudinal cracks measuring 40,80,and 120 cm in length.This systematic and rigorous approach ensures the reliability and robustness of the methodology.Ultimately,the parameters of cross-sectional area,moment of inertia,and modulus of elasticity,which significantly impact the performance of this sleeper,are explored and demonstrated through functional methodologies.The findings suggest that assessing and addressing damage should be conducted through a comprehensive and integrated procedure,taking into account the actual conditions of the PCS.Longitudinal cracks lead to a substantial decrease in the performance of these components in railway tracks.By applying the proposed methods,it is anticipated that the evaluation error for these components will be reduced by approximately 30%compared to visual inspections,particularly in predicting the extent of damage for cracks measuring up to 120 cm.This research has the potential to significantly enhance the evaluation of PCS performance and mitigate the impact of longitudinal cracks on the safety and longevity of ballasted railway tracks in desert areas.展开更多
Understanding the reinforcement effect of the newly developed prestressed reinforcement components(PRCs)(a system composed of prestressed steel bars(PSBs),protective sleeves,lateral pressure plates(LPPs),and anchoring...Understanding the reinforcement effect of the newly developed prestressed reinforcement components(PRCs)(a system composed of prestressed steel bars(PSBs),protective sleeves,lateral pressure plates(LPPs),and anchoring elements)is technically significant for the rational design of prestressed subgrade.A three-dimensional finite element model was established and verified based on a novel static model test and utilized to systematically analyze the influence of prestress levels and reinforcement modes on the reinforcement effect of the subgrade.The results show that the PRCs provide additional confining pressure to the subgrade through the diffusion effect of the prestress,which can therefore effectively improve the service performance of the subgrade.Compared to the unreinforced conventional subgrades,the settlements of prestressreinforced subgrades are reduced.The settlement attenuation rate(Rs)near the LPPs is larger than that at the subgrade center,and increasing the prestress positively contributes to the stability of the subgrade structure.In the multi-row reinforcement mode,the reinforcement effect of PRCs can extend from the reinforced area to the unreinforced area.In addition,as the horizontal distance from the LPPs increases,the additional confining pressure converted by the PSBs and LPPs gradually diminishes when spreading to the core load bearing area of the subgrade,resulting in a decrease in the Rs.Under the singlerow reinforcement mode,PRCs can be strategically arranged according to the local areas where subgrade defects readily occurred or observed,to obtain the desired reinforcement effect.Moreover,excessive prestress should not be applied near the subgrade shoulder line to avoid the shear failure of the subgrade shoulder.PRCs can be flexibly used for preventing and treating various subgrade defects of newly constructed or existing railway lines,achieving targeted and classified prevention,and effectively improving the bearing performance and deformation resistance of the subgrade.The research results are instructive for further elucidating the prestress reinforcement effect of PRCs on railway subgrades.展开更多
Critical for metering and protection in electric railway traction power supply systems(TPSSs),the measurement performance of voltage transformers(VTs)must be timely and reliably monitored.This paper outlines a three-s...Critical for metering and protection in electric railway traction power supply systems(TPSSs),the measurement performance of voltage transformers(VTs)must be timely and reliably monitored.This paper outlines a three-step,RMS data only method for evaluating VTs in TPSSs.First,a kernel principal component analysis approach is used to diagnose the VT exhibiting significant measurement deviations over time,mitigating the influence of stochastic fluctuations in traction loads.Second,a back propagation neural network is employed to continuously estimate the measurement deviations of the targeted VT.Third,a trend analysis method is developed to assess the evolution of the measurement performance of VTs.Case studies conducted on field data from an operational TPSS demonstrate the effectiveness of the proposed method in detecting VTs with measurement deviations exceeding 1%relative to their original accuracy levels.Additionally,the method accurately tracks deviation trends,enabling the identification of potential early-stage faults in VTs and helping prevent significant economic losses in TPSS operations.展开更多
Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie conditio...Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.展开更多
This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the tem...This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the temporary speed limit on the railway line and the communication delay between trains,and it uses a VCTS consisting of three trains as an experimental object.It creates the virtual coupling train tracking and control process by improving the driving strategy of the leader train and using the leader-follower model.The follower train uses the improved speed curve of the leader train as its speed refer-ence curve through knowledge migration,and this completes the multi-objective optimization of the driving strategy for the VCTS.The experimental results confirm that the deep reinforcement learning algorithm effectively achieves the optimization goal of the train driving strategy.They also reveal that the intrinsic curiosity module prioritized experience replay dueling double deep Q-network(ICM-PER-D3QN)algorithm outperforms the deep Q-network(DQN)algorithm in optimizing the driving strategy of the leader train.The ICM-PER-D3QN algorithm enhances the leader train driving strategy by an average of 57%when compared to the DQN algorithm.Furthermore,the particle swarm optimization(PSO)-based model predictive control(MPC)algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation,with an average increase of 37.7%in tracking accuracy compared to the traditional MPC algorithm.展开更多
Urban transportation systems are facing severe challenges due to the rapid growth of the urban population,especially in China.Suspended monorail system(SMS),as a sky rail transportation form,can effectively alleviate ...Urban transportation systems are facing severe challenges due to the rapid growth of the urban population,especially in China.Suspended monorail system(SMS),as a sky rail transportation form,can effectively alleviate urban traffic congestion due to its independent right-of-way and minimal ground footprint.However,the SMS possesses a special traveling system with unique vehicle structure and bridge configuration,which results in significant differences in both the mechanisms and dynamics problems associated with train–bridge interaction(TBI)when contrasted with those of traditional railway systems.Therefore,a thorough understanding of the SMS dynamics is essential for ensuring the operational safety of the system.This article presents a state-of-the-art review of the TBI modeling methodologies,critical dynamic features,field tests,and practice of the SMS in China.Firstly,the development history,technical features,and potential dynamics problems of the SMS are briefly described,followed by the mechanical characteristics and mechanisms of the train–bridge interactive systems.Then,the modeling methodology of the fundamental elements in the suspended monorail TBI is systematically reviewed,including the suspended train subsystem,bridge subsystem,train–bridge interaction relationships,system excitations,and solution method.Further,the typical dynamic features of the TBI under various operational scenarios are elaborated,including different train speeds,a variety of line sections,and a natural wind environment.Finally,the first new energy-based SMS test line in the world is systematically introduced,including the composition and functionality of the system,the details of the conducted field tests,and the measured results of the typical dynamic responses.At the end of the paper,both the guidance on further improvement of the SMS and future research topics are proposed.展开更多
Drive-by techniques for bridge health monitoring have drawn increasing attention from researchers and practitioners,in the attempt to make bridge condition-based monitoring more cost-efficient.In this work,the authors...Drive-by techniques for bridge health monitoring have drawn increasing attention from researchers and practitioners,in the attempt to make bridge condition-based monitoring more cost-efficient.In this work,the authors propose a drive-by approach that takes advantage from bogie vertical accelerations to assess bridge health status.To do so,continuous wavelet transform is combined with multiple sparse autoencoders that allow for damage detection and localization across bridge span.According to authors’best knowledge,this is the first case in which an unsupervised technique,which relies on the use of sparse autoencoders,is used to localize damages.The bridge considered in this work is a Warren steel truss bridge,whose finite element model is referred to an actual structure,belonging to the Italian railway line.To investigate damage detection and localization performances,different operational variables are accounted for:train weight,forward speed and track irregularity evolution in time.Two configurations for the virtual measuring channels were investigated:as a result,better performances were obtained by exploiting the vertical accelerations of both the bogies of the leading coach instead of using only one single acceleration signal.展开更多
Foamed concrete has been used to address the issue of differential settlement in high-speed railway subgrades in China.However,to enhance crack resistance,reinforcement is still necessary,and further research is requi...Foamed concrete has been used to address the issue of differential settlement in high-speed railway subgrades in China.However,to enhance crack resistance,reinforcement is still necessary,and further research is required to better understand the performance of foamed concrete in subgrade applications.To this end,a series of tests—including uniaxial compres-sive and dynamic triaxial tests—were conducted to comprehensively examine the effects of basalt fiber reinforcement on the mechanical properties of foamed concrete with densities of 700 and 1000 kg/m3.Additionally,a full-scale model of the foamed concrete subgrade was established,and simulated loading was applied.The diffusion patterns of dynamic stress and dynamic acceleration within the subgrade were explored,leading to the development of experimental formulas to calculate the attenuation coefficients of these two parameters along the depth and width of the subgrade.Furthermore,the dynamic displacement and cumulative settlement were analyzed to evaluate the stability of the subgrade.These findings provide valuable insights for the design and construction of foamed concrete subgrades in high-speed rail systems.The outcomes are currently under consideration for inclusion in the code of practice for high-speed rail restoration.展开更多
Railway systems are critical components of transportation networks requiring consistent maintenance.This paper proposes a novel data-driven approach to detect various maintenance needs of railway track systems using a...Railway systems are critical components of transportation networks requiring consistent maintenance.This paper proposes a novel data-driven approach to detect various maintenance needs of railway track systems using acceleration data obtained from a passenger train in operation.The framework contains four modules.Firstly,data pre-processing and cleansing are performed to extract useful data from the whole dataset.Then,condition-sensitive features are extracted from the raw data in three different domains of time,frequency,and time-frequency.In the third module,the best subset of measurement features that characterize the state of the tracks are selected using the analysis of variance(ANOVA)algorithm which eliminates irrelevant characteristics from the feature set of responses.Finally,a multilabel classification algorithm based on the cascade feed-forward neural network(CFNN)is used to classify the type of maintenance needs of the track.An open-access dataset from a field study in Pennsylvania,USA,is used in this study for validation of the proposed method.The results indicate that employing a CFNN can achieve 95%accuracy in identifying two maintenance activities,tamping and surfacing,using time-domain features.Moreover,an extensive analysis has been conducted to evaluate the influence of various feature extraction and selection methods,diverse classification algorithms,and different types of accelerometers(uni-axial and tri-axial)on the accuracy of the proposed method.展开更多
With the rapid development of heavy haul railway transportation technology,tunnel foundation defects and their effects on structural performance have attracted wide attention.This paper systematically investigates the...With the rapid development of heavy haul railway transportation technology,tunnel foundation defects and their effects on structural performance have attracted wide attention.This paper systematically investigates the evolution mechanism of tun-nel foundation defects in heavy haul railway tunnels and their impact on structural stiffness degradation through experiments and numerical simulations.A heavy haul train-ballasted track-tunnel basement-surround rock dynamic interaction model(TTTR model)is constructed.Firstly,the study reveals the four-stage evolution process of initial defects in the tunnel base-ment under complex environmental conditions.Experiments were conducted to measure the load-bearing capacity and stiff-ness degradation of the tunnel basement structure under different defect states.It is found that foundation defects,especially under the coupling of loose fill in the basement with the water-rich environment of the surrounding rock,significantly reduce the stiffness of the tunnel bottom structure and increase the risk of structural damage.Then,based on refined simulation of wheel-rail interaction and multi-scale coupled modeling technology,the TTTR dynamic interaction model was successfully constructed,and its validity was proven through numerical validation.A time-varying coupling technique of constrained boundary substructures(CBS technique)was adopted,significantly improving computational efficiency while ensuring calculation accuracy.The study also analyzes the effects of different degrees of void defects on the dynamic behavior of the train and the dynamic characteristics of the tunnel structure.It finds that foundation defects have a significant impact on the train’s operational state,track vibration displacement,and vibration stress of the tunnel lining structure,especially under the coupling effect of basement voids and the water-rich environment,which has the greatest impact.The research results of this paper provide a theoretical basis and technical support for the maintenance and reinforcement of tunnel foundation structures.展开更多
Rolling noise is an important source of railway noise and depends also on the dynamic behaviour of a railway track.This is characterized by the point or transfer mobility and the track decay rate,which depend on a num...Rolling noise is an important source of railway noise and depends also on the dynamic behaviour of a railway track.This is characterized by the point or transfer mobility and the track decay rate,which depend on a number of track parameters.One possible reason for deviations between simulated and measured results for the dynamic track behaviour is the uncertainty of the value of some track parameters used as input for the simulation.This in turn results in an uncertainty in the simulation results.In this contribution,it is proposed to use the general transformation method to assess a uncertainty band for the results.Most relevant input parameters for determining the point input mobility and the track decay rate for a ballasted track are analysed with regard to the uncertainties and for the value of each an interval is determined.Then,the general transformation method is applied to four different simulation methods,working both in the frequency and time domains.For one example track,the resulting uncertainty bands are compared to one dataset with measurements for the point mobility and the track decay rate.In addition,a sensitivity analysis is performed to determine the parameters that significantly influence the overall result.While all four simulation methods produce broad uncertainty bands for the results,none did match the measured results for the point mobility and the track decay rate over the entire frequency range considered.Besides the large influence of the uncertain pad stiffness,it turned out that the rail wear is also a significant source of uncertainty of the results.Overall,it is demonstrated that the proposed approach allows assessing the influence of uncertain input parameters in detail.展开更多
For a large-scale dynamic system,the efficiency of computation becomes a vital work sometimes in engineering practices.As a layered structural system,ballastless track and substructure occupy most part of the degrees ...For a large-scale dynamic system,the efficiency of computation becomes a vital work sometimes in engineering practices.As a layered structural system,ballastless track and substructure occupy most part of the degrees of freedom of the whole system.It is,therefore,rather important to optimize the structural models in dynamic equation formulations.In this work,a three-dimensional and coupled model for multi-rigid-body of train and finite elements of track and substructures is pre-sented by multi-scale assemble and matrix reassemble method.The matrix reassembling tactic is based on the multi-scale assemble method,through which the finite element matrix bandwidth is greatly narrowed,and the Cholesky factorization,iterative and multi-time-step solution have been introduced to efficiently obtain the train,track and substructure responses.The subgrade and its subsoil works as a typical substructural system,and comparisons with the previous model without matrix reassembling,SIMPACK and ABAQUS have been conducted to fully validate the efficiency and accuracy of this train-track-subgrade dynamic interaction model.展开更多
基金support extended by the Joint Funds of Beijing Municipal Natural Science Foundation and Fengtai Rail Transit Frontier Research(Grant No.L211006)the Fundamental Research Funds for the Central Universities(Science and technology leading talent team project,Grant No.2022JBXT010)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.2023YJS052)the National Natural Science Foundation of China(Grant No.52308426)。
文摘Investigations into rail corrugation within metro systems have traditionally focused on specific mechanisms,thereby limiting the generalizability of proposed theories.Understanding the commonalities in rail corrugation across diverse metro lines remains pivotal for elucidating its underlying mechanisms.The present study conducted extensive field surveys and tracking tests across 14 Chinese metro lines.By employing t-distributed stochastic neighbor embedding(t-SNE)for dimensional reduction and employing the unsupervised clustering algorithm DBSCAN,the research redefines the classification of metro rail corrugation based on characteristic information.The analysis encompassed spatial distribution and temporal evolution of this phenomenon.Findings revealed that floating slab tracks exhibited the highest proportion of rail corrugation at 47%.Notably,ordinary monolithic bed tracks employing damping fasteners were more prone to inducing rail corrugation.Corrugation primarily manifested in curve sections with radii between 300 and 500 m,featuring ordinary monolithic bed track and steel-spring floating slab track structures,with wavelengths typically between 30 and 120 mm.Stick–slip vibrations of the wheel–rail system maybe led to short-wavelength corrugations(40–60 mm),while longer wavelengths(200–300 mm)exhibited distinct fatigue damage characteristics,mainly observed in steel-spring floating slab tracks and small-radius curve sections of ordinary monolithic bed tracks and ladder sleeper tracks.A classification system comprising 57 correlated features categorized metro rail corrugation into four distinct types.These research outcomes serve as critical benchmarks for validating various theories pertaining to rail corrugation formation.
基金supported by the National Natural Science Foundation of China(Grant No.52272427)the Technology Research and Development Program of China National Railway Group(Grant No.K2021T015)Development Plan of China Academy of Railway Sciences Corporation Ltd.(Grant No.2022YJ256)。
文摘The China comprehensive inspection train(CIT)is designed for evaluating railway infrastructure to ensure safe railway operations.The CIT integrates an array of inspection devices,capable of simultaneously assessing railway health condition parameters.The CIT450,representing the second generation,can reach a top speed of 450 km/h with inspection on the infrastructure.This paper begins by outlining the global evolution of inspection trains.It then focuses on the critical technologies underlying the CIT450,which include:(1)real-time inspection data acquisition with spatial and temporal synchronization;(2)intelligent fusion and centralized management of multi-source inspection data,enabling remote supervision of the inspection process;(3)technologies in inspecting track,train–track interaction,catenary,signalling systems,and train operating environment;and(4)AI-driven analysis and correlation of inspection data.The future developmental directions for comprehensive inspection trains are discussed finally.The CIT450’s approach to real-time railway health monitoring can enrich traditional inspection means,operational,and maintenance methods by enhancing inspection efficiency and automating railway maintenance.
文摘The Third International Conference on Rail Transportation(ICRT),which was initiated by Southwest Jiaotong University and hosted by Tongji University,took place successfully in Shanghai,China,from August 7 to 9,2024.As the chairman of the ICRT conference,I am delighted to witness its remarkable achievement.Based on the success of previous editions held in Chengdu in 2017 and 2021,this conference aims to provide a premier platform for extensive interaction and collaboration among universities,research institutions,and enterprises worldwide.
文摘Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions must be carefully considered throughout their life cycle.Recent advancements in science and technology have enabled more effective structural monitoring of railway systems,largely driven by the adoption of intelligent strategies for inspection,maintenance,monitoring,and risk management.Research continues to expand and deepen the knowledge in this area;however,it remains a challenging field due to factors such as the complexity of railway systems,the high cost of implementation,and the need for reliable long-term data.
文摘Replacing the energy density and convenience of diesel fuel for all forms of fossil fuel-powered trains presents significant challenges.Unlike the traditional evolutions of rail which has largely self-optimised to different fuels and cost structures over 150 years,the challenges now present with a timeline of just a few decades.Fortunately,unlike the mid-1800s,simulation and modelling tools are now quite advanced and a full range of scenarios of operations and train trips can be simulated before new traction systems are designed.Full trip simulations of large heavy haul trains or high speed passenger trains are routinely completed controlled by emulations of human drivers or automated control systems providing controls of the“virtual train”.Recent developments in digital twins can be used to develop flexible and dynamic models of passenger and freight rail systems to support the new complexities of decarbonisation efforts.Interactions between many different traction components and the train multibody system can be considered as a system of systems.Adopting this multi-modelling paradigm enables the secure and integrated interfacing of diverse models.This paper demonstrates the application of the multi-modelling approach to develop digital twins for rail decarbonisation traction and it presents physics-based multi-models that include key components required for studying rail decarbonisation problems.Specifically,the challenge of evaluating zero-emission options is addressed by adding further layers of modelling to the existing fully detailed multibody dynamics simulations.The additional layers detail control options,energy storage,the alternate traction system components and energy management systems.These traction system components may include both electrical system and inertia dynamics models to accurately represent the driveline and control systems.This paper presents case study examples of full trip scenarios of both long haul freight trains and higher speed passenger trains.These results demonstrate the many complex scenarios that are difficult to anticipate.Flowing on from this,risks can be assessed and practical designs of zero-emission systems can be proposed along with the required recharging or refuelling systems.
基金the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4-Call for tender No. 3138 of 16/12/2021 of Italian Ministry of University and Research funded by the European Union-Next Generation EU. Award Number: Project code CN00000023Concession Decree No. 1033 of 17/06/2022 adopted by the Italian Ministry of University and Research, CUP D93C22000400001, “Sustainable Mobility Center” (CNMS). Spoke 4-Rail Transportation
文摘Predictive maintenance is essential for the implementation of an innovative and efficient structural health monitoring strategy.Models capable of accurately interpreting new data automatically collected by suitably placed sensors to assess the state of the infrastructure represent a fundamental step,particularly for the railway sector,whose safe and continuous operation plays a strategic role in the well-being and development of nations.In this scenario,the benefits of a digital twin of a bonded insu-lated rail joint(IRJ)with the predictive capabilities of advanced classification algorithms based on artificial intelligence have been explored.The digital model provides an accurate mechanical response of the infrastructure as a pair of wheels passes over the joint.As bolt preload conditions vary,four structural health classes were identified for the joint.Two parameters,i.e.gap value and vertical displacement,which are strongly correlated with bolt preload,are used in different combinations to train and test five predictive classifiers.Their classification effectiveness was assessed using several performance indica-tors.Finally,we compared the IRJ condition predictions of two trained classifiers with the available data,confirming their high accuracy.The approach presented provides an interesting solution for future predictive tools in SHM especially in the case of complex systems such as railways where the vehicle-infrastructure interaction is complex and always time varying.
基金supported by the German Research Foundation(DFG)under the project“Efficient Sensor-Based Condition Monitoring Methodology for the Detection and Localization of Faults on the Railway Track(ConMoRAIL)”,Grant No.515687155.
文摘Supervised learning classification has arisen as a powerful tool to perform data-driven fault diagnosis in dynamical systems,achieving astonishing results.This approach assumes the availability of extensive,diverse and labeled data corpora for train-ing.However,in some applications it may be difficult or not feasible to obtain a large and balanced dataset including enough representative instances of the fault behaviors of interest.This fact leads to the issues of data scarcity and class imbalance,greatly affecting the performance of supervised learning classifiers.Datasets from railway systems are usually both,scarce and imbalanced,turning supervised learning-based fault diagnosis into a highly challenging task.This article addresses time-series data augmentation for fault diagnosis purposes and presents two application cases in the context of railway track.The case studies employ generative adversarial networks(GAN)schemes to produce realistic synthetic samples of geometrical and structural track defects.The goal is to generate samples that enhance fault diagnosis performance;therefore,major attention was paid not only in the generation process,but also in the synthesis quality assessment,to guarantee the suitability of the samples for training of supervised learning classification models.In the first application,a convolutional classifier achieved a test accuracy of 87.5%for the train on synthetic,test on real(TSTR)scenario,while,in the second application,a fully-connected classifier achieved 96.18%in test accuracy for TSTR.The results indicate that the proposed augmentation approach produces samples having equivalent statistical characteristics and leading to a similar classification behavior as real data.
基金supported in part by the National Natural Science Foundation of China under Grant No.52277126.
文摘The integration of a large number of power electronic converters,such as railway power conditioner(RPC),introduces a series of problems,including harmonic interaction,stability issues,and wideband resonance,into the railway power supply system.To address these challenges,this paper proposes a novel harmonic resonance prevention measure for RPC-network-train interaction system.Firstly,a harmonic model,a parallel resonance impedance model,a series resonance admittance model,and a control stability model are each established for the RPC-network-train interaction system.Secondly,a comprehensive resonance impact factor(CRIF)is proposed to efficiently and accurately identify the key components affecting resonance,and to provide the selection results of optimization parameters for resonance prevention.Next,the initially selected parameters are constrained by the requirements of ripple current,reactive power and stability.Subsequently,the impedance parameters(control parameters and filter parameters)of the RPC are optimized with the objective of reshaping the parallel resonance impedance and series resonance admittance of the RPC-network-train interaction system,ensuring the output current har-monics of RPC meet standards to achieve resonance prevention,while ensuring the stable operation of the RPC.Finally,the proposed resonance prevention measure is verified under both light load and heavy load conditions using a simulation platform and a hardware-in-the-loop experimental platform.
文摘The operational and regional conditions to which the prestressed concrete sleeper(PCS)is subjected in a railway track significantly contribute to its performance and durability.Maintaining the health of PCS poses challenges,and one of these issues involves the potential occurrence of longitudinal cracks in reinforcing bars,which can be caused by various constructional,functional,and environmental factors.Longitudinal cracks in PCS compromise the structural performance,resulting in a reduced capacity to withstand the loads exerted by moving vehicles.The current evaluations not only fail to yield a precise parameter for estimating the behavior and response of the PCS,but they also overlook the specific conditions of the PCS,such as prestressing,and only provide limited information regarding existing damage.Balancing the need for accurate evaluation with consideration of costs and resources,and making informed decisions about maintenance and track performance enhancement,has become a multifaceted challenge in ensuring a robust PCS assessment.This research introduces a novel methodology to improve the evaluation of mechanical and geometrical parameters of PCS over their operational lifespan.The objective is to enhance the accuracy of PCS performance estimation by concentrating on detecting longitudinal cracks.The suggested approach seamlessly integrates model updating methods and the finite element(FE)approach to achieve an accurate and timely assessment of PCS conditions.This comprehensive examination scrutinizes the methodology by applying artificial cracks to the PCS.In addition to introducing this assessment approach,a detailed examination is conducted on a laboratory-simulated PCS featuring various combinations of longitudinal cracks measuring 40,80,and 120 cm in length.This systematic and rigorous approach ensures the reliability and robustness of the methodology.Ultimately,the parameters of cross-sectional area,moment of inertia,and modulus of elasticity,which significantly impact the performance of this sleeper,are explored and demonstrated through functional methodologies.The findings suggest that assessing and addressing damage should be conducted through a comprehensive and integrated procedure,taking into account the actual conditions of the PCS.Longitudinal cracks lead to a substantial decrease in the performance of these components in railway tracks.By applying the proposed methods,it is anticipated that the evaluation error for these components will be reduced by approximately 30%compared to visual inspections,particularly in predicting the extent of damage for cracks measuring up to 120 cm.This research has the potential to significantly enhance the evaluation of PCS performance and mitigate the impact of longitudinal cracks on the safety and longevity of ballasted railway tracks in desert areas.
基金supported by the National Natural Science Foundation of China(Grant Nos.51978672 and 52308335)the Natural Science Funding of Hunan Province(Grant No.2023JJ41054)the Natural Science Research Project of Anhui Educational Committee(Grant No.2023AH051170)。
文摘Understanding the reinforcement effect of the newly developed prestressed reinforcement components(PRCs)(a system composed of prestressed steel bars(PSBs),protective sleeves,lateral pressure plates(LPPs),and anchoring elements)is technically significant for the rational design of prestressed subgrade.A three-dimensional finite element model was established and verified based on a novel static model test and utilized to systematically analyze the influence of prestress levels and reinforcement modes on the reinforcement effect of the subgrade.The results show that the PRCs provide additional confining pressure to the subgrade through the diffusion effect of the prestress,which can therefore effectively improve the service performance of the subgrade.Compared to the unreinforced conventional subgrades,the settlements of prestressreinforced subgrades are reduced.The settlement attenuation rate(Rs)near the LPPs is larger than that at the subgrade center,and increasing the prestress positively contributes to the stability of the subgrade structure.In the multi-row reinforcement mode,the reinforcement effect of PRCs can extend from the reinforced area to the unreinforced area.In addition,as the horizontal distance from the LPPs increases,the additional confining pressure converted by the PSBs and LPPs gradually diminishes when spreading to the core load bearing area of the subgrade,resulting in a decrease in the Rs.Under the singlerow reinforcement mode,PRCs can be strategically arranged according to the local areas where subgrade defects readily occurred or observed,to obtain the desired reinforcement effect.Moreover,excessive prestress should not be applied near the subgrade shoulder line to avoid the shear failure of the subgrade shoulder.PRCs can be flexibly used for preventing and treating various subgrade defects of newly constructed or existing railway lines,achieving targeted and classified prevention,and effectively improving the bearing performance and deformation resistance of the subgrade.The research results are instructive for further elucidating the prestress reinforcement effect of PRCs on railway subgrades.
基金supported by the National Natural Science Foundation of China(No.52107125)Applied Basic Research Project of Sichuan Province(No.2022NSFSC0250)Chengdu Guojia Electrical Engineering Co.,Ltd.(No.KYL202312-0043).
文摘Critical for metering and protection in electric railway traction power supply systems(TPSSs),the measurement performance of voltage transformers(VTs)must be timely and reliably monitored.This paper outlines a three-step,RMS data only method for evaluating VTs in TPSSs.First,a kernel principal component analysis approach is used to diagnose the VT exhibiting significant measurement deviations over time,mitigating the influence of stochastic fluctuations in traction loads.Second,a back propagation neural network is employed to continuously estimate the measurement deviations of the targeted VT.Third,a trend analysis method is developed to assess the evolution of the measurement performance of VTs.Case studies conducted on field data from an operational TPSS demonstrate the effectiveness of the proposed method in detecting VTs with measurement deviations exceeding 1%relative to their original accuracy levels.Additionally,the method accurately tracks deviation trends,enabling the identification of potential early-stage faults in VTs and helping prevent significant economic losses in TPSS operations.
基金a U.S. Federal Railroad Administration (FRA)BAA project,titled “Mitigation of Differential Movement at Railway Transitions for High-Speed Passenger Rail and Joint Passenger/Freight Corridors”the financial support provided by the China Scholarship Council (CSC),which funded Zhongyi Liu’s and Wenjing Li’s time and research efforts for this study
文摘Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.
基金supported by the National Natural Science Foundation of China under Grant 52162050.
文摘This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the temporary speed limit on the railway line and the communication delay between trains,and it uses a VCTS consisting of three trains as an experimental object.It creates the virtual coupling train tracking and control process by improving the driving strategy of the leader train and using the leader-follower model.The follower train uses the improved speed curve of the leader train as its speed refer-ence curve through knowledge migration,and this completes the multi-objective optimization of the driving strategy for the VCTS.The experimental results confirm that the deep reinforcement learning algorithm effectively achieves the optimization goal of the train driving strategy.They also reveal that the intrinsic curiosity module prioritized experience replay dueling double deep Q-network(ICM-PER-D3QN)algorithm outperforms the deep Q-network(DQN)algorithm in optimizing the driving strategy of the leader train.The ICM-PER-D3QN algorithm enhances the leader train driving strategy by an average of 57%when compared to the DQN algorithm.Furthermore,the particle swarm optimization(PSO)-based model predictive control(MPC)algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation,with an average increase of 37.7%in tracking accuracy compared to the traditional MPC algorithm.
基金supported by the National Natural Science Foundation of China(Grant Nos.52202483,52108476,and 52388102)。
文摘Urban transportation systems are facing severe challenges due to the rapid growth of the urban population,especially in China.Suspended monorail system(SMS),as a sky rail transportation form,can effectively alleviate urban traffic congestion due to its independent right-of-way and minimal ground footprint.However,the SMS possesses a special traveling system with unique vehicle structure and bridge configuration,which results in significant differences in both the mechanisms and dynamics problems associated with train–bridge interaction(TBI)when contrasted with those of traditional railway systems.Therefore,a thorough understanding of the SMS dynamics is essential for ensuring the operational safety of the system.This article presents a state-of-the-art review of the TBI modeling methodologies,critical dynamic features,field tests,and practice of the SMS in China.Firstly,the development history,technical features,and potential dynamics problems of the SMS are briefly described,followed by the mechanical characteristics and mechanisms of the train–bridge interactive systems.Then,the modeling methodology of the fundamental elements in the suspended monorail TBI is systematically reviewed,including the suspended train subsystem,bridge subsystem,train–bridge interaction relationships,system excitations,and solution method.Further,the typical dynamic features of the TBI under various operational scenarios are elaborated,including different train speeds,a variety of line sections,and a natural wind environment.Finally,the first new energy-based SMS test line in the world is systematically introduced,including the composition and functionality of the system,the details of the conducted field tests,and the measured results of the typical dynamic responses.At the end of the paper,both the guidance on further improvement of the SMS and future research topics are proposed.
文摘Drive-by techniques for bridge health monitoring have drawn increasing attention from researchers and practitioners,in the attempt to make bridge condition-based monitoring more cost-efficient.In this work,the authors propose a drive-by approach that takes advantage from bogie vertical accelerations to assess bridge health status.To do so,continuous wavelet transform is combined with multiple sparse autoencoders that allow for damage detection and localization across bridge span.According to authors’best knowledge,this is the first case in which an unsupervised technique,which relies on the use of sparse autoencoders,is used to localize damages.The bridge considered in this work is a Warren steel truss bridge,whose finite element model is referred to an actual structure,belonging to the Italian railway line.To investigate damage detection and localization performances,different operational variables are accounted for:train weight,forward speed and track irregularity evolution in time.Two configurations for the virtual measuring channels were investigated:as a result,better performances were obtained by exploiting the vertical accelerations of both the bogies of the leading coach instead of using only one single acceleration signal.
基金support for this research from the Fundamental Research Funds for the National Natural Science Foundation of China (Grant Nos. 51978588, 52078434, and 52368065)the China Scholarship Council (Grant No. 202107000077)UKRI Engineering and Physical Science ResearchCouncil (EPSRC) for the financial sponsorship of Re4Rail project (Grant No. EP/Y015401/1)
文摘Foamed concrete has been used to address the issue of differential settlement in high-speed railway subgrades in China.However,to enhance crack resistance,reinforcement is still necessary,and further research is required to better understand the performance of foamed concrete in subgrade applications.To this end,a series of tests—including uniaxial compres-sive and dynamic triaxial tests—were conducted to comprehensively examine the effects of basalt fiber reinforcement on the mechanical properties of foamed concrete with densities of 700 and 1000 kg/m3.Additionally,a full-scale model of the foamed concrete subgrade was established,and simulated loading was applied.The diffusion patterns of dynamic stress and dynamic acceleration within the subgrade were explored,leading to the development of experimental formulas to calculate the attenuation coefficients of these two parameters along the depth and width of the subgrade.Furthermore,the dynamic displacement and cumulative settlement were analyzed to evaluate the stability of the subgrade.These findings provide valuable insights for the design and construction of foamed concrete subgrades in high-speed rail systems.The outcomes are currently under consideration for inclusion in the code of practice for high-speed rail restoration.
基金supported by Research Ireland under Grant No.20/FFP-P/8706.
文摘Railway systems are critical components of transportation networks requiring consistent maintenance.This paper proposes a novel data-driven approach to detect various maintenance needs of railway track systems using acceleration data obtained from a passenger train in operation.The framework contains four modules.Firstly,data pre-processing and cleansing are performed to extract useful data from the whole dataset.Then,condition-sensitive features are extracted from the raw data in three different domains of time,frequency,and time-frequency.In the third module,the best subset of measurement features that characterize the state of the tracks are selected using the analysis of variance(ANOVA)algorithm which eliminates irrelevant characteristics from the feature set of responses.Finally,a multilabel classification algorithm based on the cascade feed-forward neural network(CFNN)is used to classify the type of maintenance needs of the track.An open-access dataset from a field study in Pennsylvania,USA,is used in this study for validation of the proposed method.The results indicate that employing a CFNN can achieve 95%accuracy in identifying two maintenance activities,tamping and surfacing,using time-domain features.Moreover,an extensive analysis has been conducted to evaluate the influence of various feature extraction and selection methods,diverse classification algorithms,and different types of accelerometers(uni-axial and tri-axial)on the accuracy of the proposed method.
基金funded by the National Natural Science Foundation of China (Grant No. 52178402 & 52378468)the Open Foundation of MOE Key Laboratory of Engineering Structures of Heavy Haul Railway (Central South University) (Grant No. 2022JZZ01)+1 种基金the National Engineering Research Center for High-Speed Railway Construction Technology for their project supportthe support from the MOE Key Laboratory of Engineering Structure of Heavy Haul Railway (Central South University)
文摘With the rapid development of heavy haul railway transportation technology,tunnel foundation defects and their effects on structural performance have attracted wide attention.This paper systematically investigates the evolution mechanism of tun-nel foundation defects in heavy haul railway tunnels and their impact on structural stiffness degradation through experiments and numerical simulations.A heavy haul train-ballasted track-tunnel basement-surround rock dynamic interaction model(TTTR model)is constructed.Firstly,the study reveals the four-stage evolution process of initial defects in the tunnel base-ment under complex environmental conditions.Experiments were conducted to measure the load-bearing capacity and stiff-ness degradation of the tunnel basement structure under different defect states.It is found that foundation defects,especially under the coupling of loose fill in the basement with the water-rich environment of the surrounding rock,significantly reduce the stiffness of the tunnel bottom structure and increase the risk of structural damage.Then,based on refined simulation of wheel-rail interaction and multi-scale coupled modeling technology,the TTTR dynamic interaction model was successfully constructed,and its validity was proven through numerical validation.A time-varying coupling technique of constrained boundary substructures(CBS technique)was adopted,significantly improving computational efficiency while ensuring calculation accuracy.The study also analyzes the effects of different degrees of void defects on the dynamic behavior of the train and the dynamic characteristics of the tunnel structure.It finds that foundation defects have a significant impact on the train’s operational state,track vibration displacement,and vibration stress of the tunnel lining structure,especially under the coupling effect of basement voids and the water-rich environment,which has the greatest impact.The research results of this paper provide a theoretical basis and technical support for the maintenance and reinforcement of tunnel foundation structures.
文摘Rolling noise is an important source of railway noise and depends also on the dynamic behaviour of a railway track.This is characterized by the point or transfer mobility and the track decay rate,which depend on a number of track parameters.One possible reason for deviations between simulated and measured results for the dynamic track behaviour is the uncertainty of the value of some track parameters used as input for the simulation.This in turn results in an uncertainty in the simulation results.In this contribution,it is proposed to use the general transformation method to assess a uncertainty band for the results.Most relevant input parameters for determining the point input mobility and the track decay rate for a ballasted track are analysed with regard to the uncertainties and for the value of each an interval is determined.Then,the general transformation method is applied to four different simulation methods,working both in the frequency and time domains.For one example track,the resulting uncertainty bands are compared to one dataset with measurements for the point mobility and the track decay rate.In addition,a sensitivity analysis is performed to determine the parameters that significantly influence the overall result.While all four simulation methods produce broad uncertainty bands for the results,none did match the measured results for the point mobility and the track decay rate over the entire frequency range considered.Besides the large influence of the uncertain pad stiffness,it turned out that the rail wear is also a significant source of uncertainty of the results.Overall,it is demonstrated that the proposed approach allows assessing the influence of uncertain input parameters in detail.
基金supported by the National Natural Science Foundation of China(Grant Nos.52378468)Science and Technology Research and Development Program Project of China railway group limited(Major Special Project,No.2022-Major-14,2021-Special-08,2021-Major-02)+3 种基金Young Elite Scientists Sponsorship Program by CAST(2020-2022QNRC002)Central South University Innovation-Driven Research Programme(2023CXQD073)the National Natural Science Foundation of Hunan Province(Grant Nos.2022JJ20071 and 2021JJ30850)National Key R&D Program‘Transportation Infrastructure’‘Reveal the list and take command’project(2022YFB2603301).
文摘For a large-scale dynamic system,the efficiency of computation becomes a vital work sometimes in engineering practices.As a layered structural system,ballastless track and substructure occupy most part of the degrees of freedom of the whole system.It is,therefore,rather important to optimize the structural models in dynamic equation formulations.In this work,a three-dimensional and coupled model for multi-rigid-body of train and finite elements of track and substructures is pre-sented by multi-scale assemble and matrix reassemble method.The matrix reassembling tactic is based on the multi-scale assemble method,through which the finite element matrix bandwidth is greatly narrowed,and the Cholesky factorization,iterative and multi-time-step solution have been introduced to efficiently obtain the train,track and substructure responses.The subgrade and its subsoil works as a typical substructural system,and comparisons with the previous model without matrix reassembling,SIMPACK and ABAQUS have been conducted to fully validate the efficiency and accuracy of this train-track-subgrade dynamic interaction model.
