Special Issue "Monitoring and Maintenance Systems for Railway Infrastructure"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 31 March 2021.

Special Issue Editor

Dr. Alfredo Núñez
Website
Guest Editor
Section of Railway Engineering, Department of Engineering Structures, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, 2628CN, The Netherlands
Interests: railway engineering; monitoring of railway infrastructure; modeling of railway infrastructure systems; maintenance strategies for railway systems; transportation networks; model predictive control; computational intelligence; fuzzy systems

Special Issue Information

Dear colleagues,

In recent years, various aspects of the railway industry have shown major progress, including the development and application of various new technologies that have facilitated the daily operations of railway systems. Monitoring and maintenance are among the crucial activities that have benefited from these developments. Sensor technologies have allowed the collection of massive amounts of distributed railway infrastructure data. One actual challenge is understanding the relationships between different sources of data and the actual condition of the railway system. Monitoring data are crucial for the design of a maintenance strategy that allows intervention in the infrastructure when, for instance, defects in the catenary or railway track are detected. Maintenance strategies should be tailored to local conditions, minimize the safety and disruption risks, and reduce costs, while ensuring the robustness, sustainability, among other key objectives, for a railway system.

In the railway infrastructure monitoring and maintenance literature, various methods have been proposed. This Special Issue aims to gather contributions oriented toward the design and implementation of both monitoring and maintenance solutions for railway infrastructure systems. We invite contributions on topics related to all aspects of monitoring and maintenance of railway infrastructure, which include, but are not limited to, the following:

  • New sensors and measurements for monitoring the health condition of railway systems;
  • Detection of defects in railway infrastructure assets such as railway tracks, catenary systems, level crossings, rolling stock, etc.;
  • Effective monitoring of railway infrastructure including data-based methods, physical-model-based methods, and hybrid methods;
  • Modelling of railway system dynamics and degradation for defining new condition monitoring strategies;
  • Novel maintenance strategies including optimization-based approaches, intelligence-based methods, expert systems, and heuristics;
  • Design of railway system performance indicators;
  • Modelling the impact of disruptions and design and rescheduling of timetables;
  • Architecture design for railway big data streaming, processing, and management; and
  • Big data approaches to railway infrastructure monitoring and maintenance.
  • Artificial Intelligence approaches for railway infrastructure monitoring and maintenance, including various aspects of railway operations.

Dr. Alfredo Núñez
Guest Editor

Manuscript Submission Information

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Keywords

  • railway engineering
  • railway monitoring
  • railway maintenance
  • railway modelling
  • sensors for railway systems

Published Papers (15 papers)

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Research

Open AccessArticle
Train Wheel Condition Monitoring via Cepstral Analysis of Axle Box Accelerations
Appl. Sci. 2021, 11(4), 1432; https://doi.org/10.3390/app11041432 - 05 Feb 2021
Viewed by 248
Abstract
Continuous wheel condition monitoring is indispensable for the early detection of wheel defects. In this paper, we provide an approach based on cepstral analysis of axle-box accelerations (ABA). It is applied to the data in the spatial domain, which is why we introduce [...] Read more.
Continuous wheel condition monitoring is indispensable for the early detection of wheel defects. In this paper, we provide an approach based on cepstral analysis of axle-box accelerations (ABA). It is applied to the data in the spatial domain, which is why we introduce a new data representation called navewumber domain. In this domain, the wheel circumference and hence the wear of the wheel can be monitored. Furthermore, the amplitudes of peaks in the navewumber domain indicate the severity of possible wheel defects. We demonstrate our approach on simple synthetic data and real data gathered with an on-board multi-sensor system. The speed information obtained from fusing global navigation satellite system (GNSS) and inertial measurement unit (IMU) data is used to transform the data from time to space. The data acquisition was performed with a measurement train under normal operating conditions in the mainline railway network of Austria. We can show that our approach provides robust features that can be used for on-board wheel condition monitoring. Therefore, it enables further advances in the field of condition based and predictive maintenance of railway wheels. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Prediction of Rolling Contact Fatigue Behavior in Rails Using Crack Initiation and Growth Models along with Multibody Simulations
Appl. Sci. 2021, 11(3), 1026; https://doi.org/10.3390/app11031026 - 23 Jan 2021
Viewed by 365
Abstract
Rolling contact fatigue (RCF) is a common cause of rail failure due to repeated stresses at the wheel-rail contact. This phenomenon is a real problem that greatly affects the safety of train operation. Preventive and corrective maintenance tasks have a big impact on [...] Read more.
Rolling contact fatigue (RCF) is a common cause of rail failure due to repeated stresses at the wheel-rail contact. This phenomenon is a real problem that greatly affects the safety of train operation. Preventive and corrective maintenance tasks have a big impact on the Life Cycle Cost (LCC) of railway assets, and therefore cutting-edge strategies based on predictive functionalities are needed to reduce it. A methodology based on physical models is proposed to predict the degradation of railway tracks due to RCF. This work merges a crack initiation and a crack growth model along with a fully nonlinear multibody model. From a multibody assessment of the vehicle-track interaction, an energy dissipation method is used to identify points where cracks are expected to appear. At these points, crack propagation is calculated considering the contact conditions as a function of crack depth. The proposed methodology has been validated with field measurements, conducted using Eddy Currents provided by the infrastructure manager Network Rail. Validation results show that RCF behavior can be predicted for track sections with different characteristics without the necessity of previous on-track measurements. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Realisation of a Novel Functionally Redundant Actuation System for a Railway Track-Switch
Appl. Sci. 2021, 11(2), 702; https://doi.org/10.3390/app11020702 - 13 Jan 2021
Viewed by 360
Abstract
This paper focuses on modelling, control, realisation and performance analysis of a full-scale demonstrator for a novel railway track switch. For over a century, railway track switches (or points) have been allowing trains to safely change between routes. As they are safety-critical elements [...] Read more.
This paper focuses on modelling, control, realisation and performance analysis of a full-scale demonstrator for a novel railway track switch. For over a century, railway track switches (or points) have been allowing trains to safely change between routes. As they are safety-critical elements of the rail network, when they fail, the signalling system will prevent trains from using that route. This means poor reliability (or lack of availability) leads to significant delays and costs; hence there is huge interest from researchers and engineers in improving the overall reliability of track switches. This paper presents new results, which represent a meaningful first step toward a revolution in the way track switches are actuated. A “REPOINT-Light” railway track switch demonstrator is introduced which uses a new concept of locking to allow redundant actuation with three actuator bearers operating under closed-loop feedback control. The new concept, its control system and its mechanical viability are tested in experiments at the Great Central Railway in the UK. To support the design of the actuators and the control system, a dynamic simulation model is developed by co-simulation involving Simulink and Simpack. The experimental results presented are used to validate the models and the paper discusses how the models themselves are used as the vehicle for the design of feedback controllers. Virtual testing of the controllers in simulation is a vital step prior to the implementation and deployment of the controllers in the demonstrator switch. The major contribution of this work is demonstrating, for the first time at full scale on a real-world track switch, that it is possible to use one-out-of-three actuator redundancy to provide fault-tolerant operation of railway track switch. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
An Improved Cohesive Zone Model for Interface Mixed-Mode Fractures of Railway Slab Tracks
Appl. Sci. 2021, 11(1), 456; https://doi.org/10.3390/app11010456 - 05 Jan 2021
Viewed by 371
Abstract
The interface crack of a slab track is a fracture of mixed-mode that experiences a complex loading–unloading–reloading process. A reasonable simulation of the interaction between the layers of slab tracks is the key to studying the interface crack. However, the existing models of [...] Read more.
The interface crack of a slab track is a fracture of mixed-mode that experiences a complex loading–unloading–reloading process. A reasonable simulation of the interaction between the layers of slab tracks is the key to studying the interface crack. However, the existing models of interface disease of slab track have problems, such as the stress oscillation of the crack tip and self-repairing, which do not simulate the mixed mode of interface cracks accurately. Aiming at these shortcomings, we propose an improved cohesive zone model combined with an unloading/reloading relationship based on the original Park–Paulino–Roesler (PPR) model in this paper. It is shown that the improved model guaranteed the consistency of the cohesive constitutive model and described the mixed-mode fracture better. This conclusion is based on the assessment of work-of-separation and the simulation of the mixed-mode bending test. Through the test of loading, unloading, and reloading, we observed that the improved unloading/reloading relationship effectively eliminated the issue of self-repairing and preserved all essential features. The proposed model provides a tool for the study of interface cracking mechanism of ballastless tracks and theoretical guidance for the monitoring, maintenance, and repair of layer defects, such as interfacial cracks and slab arches. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
The Mkurtogram: A Novel Method to Select the Optimal Frequency Band in the AC Domain for Railway Wheelset Bearings Fault Diagnosis
Appl. Sci. 2021, 11(1), 9; https://doi.org/10.3390/app11010009 - 22 Dec 2020
Viewed by 424
Abstract
A wheelset bearing is one of the main components of the train bogie frame. The early fault detection of the wheelset bearing is quite important to ensure the safety of the train. Among numerous diagnostic methods, envelope analysis is one of the most [...] Read more.
A wheelset bearing is one of the main components of the train bogie frame. The early fault detection of the wheelset bearing is quite important to ensure the safety of the train. Among numerous diagnostic methods, envelope analysis is one of the most effective approaches in the detection of bearing faults which has been amply applied, but its validity greatly depends on the informative frequency band (IFB) determined. For the wheelset bearing faulty signal, it is often difficult to identify the IFB and extract fault characteristics due to the influence of complex operating conditions. To address this problem, a novel method to select optimal IFB, called the Mkurtogram, is proposed for railway wheelset bearings fault diagnosis. It takes the multipoint kurtosis (Mkurt) of unbiased autocorrelation (AC) of the squared envelope signal generated from sub-bands as assessment indicator for the first time. The fundamental concept which inspires this proposed method is to make full use of regular periodicity of AC of squared envelope signal. In the AC domain, the impulsiveness and periodicity, two distinctive signatures of the repetitive transients, have achieved a united representation by Mkurt. A simulated signal with multiple interferences and two experimental signals collected from wheelset bearings are applied to verify its performances and advantages. The results indicate that the proposed method is more effective to extract the wheelset bearings fault feature under complex interferences. It can not only decrease the influence of large impulse interference and the discrete harmonics interference, but also effectively overcome the influence of amplitude fluctuation caused by variable working conditions. Moreover, based on the periodic directivity of Mkurt, the proposed method also can be applied to the compound faults diagnosis of the wheelset bearing. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Developing Machine Learning-Based Models for Railway Inspection
Appl. Sci. 2021, 11(1), 13; https://doi.org/10.3390/app11010013 - 22 Dec 2020
Cited by 2 | Viewed by 428
Abstract
Smart railway maintenance is crucial to the safety and efficiency of railway operations. Successful deployment of technologies such as condition-based monitoring and predictive maintenance will enable railway companies to conduct proactive maintenance before defects and failures take place to improve operation safety and [...] Read more.
Smart railway maintenance is crucial to the safety and efficiency of railway operations. Successful deployment of technologies such as condition-based monitoring and predictive maintenance will enable railway companies to conduct proactive maintenance before defects and failures take place to improve operation safety and efficiency. In this paper, we first propose to develop a classification-based method to detect rail defects such as localized surface collapse, rail end batter, or rail components—such as joints, turning points, crossings, etc.—by using acceleration data. In order to improve the performance of the classification-based models and enhance their applicability in practice, we further propose a deep learning-based approach for the detection of rail joints or defects by deploying convolutional neural networks (CNN). CNN-based models can work directly with raw data to reduce the heavy preprocessing of feature engineering and directly detect joints located on either the left or the right rail. Two convolutional networks, ResNet and fully convolutional networks (FCN), are investigated and evaluated with the collected acceleration data. The experimental results show both deep neural networks obtain good performance, which demonstrate that the deep learning-based methods are effective for detecting rail joints or defects with the expected performance. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Analyzing Major Track Quality Indices and Introducing a Universally Applicable TQI
Appl. Sci. 2020, 10(23), 8490; https://doi.org/10.3390/app10238490 - 27 Nov 2020
Viewed by 526
Abstract
Adequate railway track condition is a prerequisite for safe and reliable railway operation. Many track quality indices (TQIs) have been developed with the aim of assessing the track condition holistically. These indices combine measurement signals of some or all relevant geometry parameters with [...] Read more.
Adequate railway track condition is a prerequisite for safe and reliable railway operation. Many track quality indices (TQIs) have been developed with the aim of assessing the track condition holistically. These indices combine measurement signals of some or all relevant geometry parameters with different mathematical models. In this paper, a selection of important TQIs is evaluated. Using measurement data of a five kilometer track section, the indices are calculated and their properties are discussed. This study reveals that all indices exhibit drawbacks to varying degrees. As a consequence, a new index has been developed—the track quality index of Graz University of Technology (TUG_TQI). Its favorable characteristics are presented by means of the above-mentioned test section. The TUG_TQI combines all relevant track geometry parameters, which are normalized beforehand to eliminate over or underrepresentation of different parameters. Thus, the index reliably describes the overall geometrical track quality. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Study on the Applicability of Dynamic Factor Standards by Comparison of Spring Constant Based Dynamic Factor of Ballasted and Concrete Track Structures
Appl. Sci. 2020, 10(23), 8361; https://doi.org/10.3390/app10238361 - 25 Nov 2020
Viewed by 329
Abstract
Dynamic factor evaluation method calculation methods outlined by Eisenmann (DAFEisenmann) and the American Railway Engineering Association (DAFArea) are used to calculate the dynamic factor during design and for trackside measurement, respectively, in nations where the construction of concrete track [...] Read more.
Dynamic factor evaluation method calculation methods outlined by Eisenmann (DAFEisenmann) and the American Railway Engineering Association (DAFArea) are used to calculate the dynamic factor during design and for trackside measurement, respectively, in nations where the construction of concrete track structures is relatively new. In this situation, dynamic factor calculation methods may be incorrect, and this is demonstrated by comparison of the respective track types’ total spring constant. A finite element analysis of a standard design railway track is conducted, and the design total spring constant (TSC, or K) obtained from the time history function analysis is compared to the TSC of existing tracks through trackside measurement results. The comparison result shows that TSC obtained by finite element analysis result is 22% higher than that of the trackside measurement value, indicating that the TSC is conservative in the current track design. Considering the proportional relationship between TSC and dynamic factor, it is estimated that the dynamic factor currently being applied in track design is also conservative. Based on these findings, an assessment of the applicability of different dynamic factors (DAFEisenmann and DAFArea), theoretical calculation and field measurement (DAFField) using the probabilistic analysis of wheel loads from the field measurement data is conducted. A correlative analysis between DAFEisenmann and DAFArea shows that DAFEisenmann and DAFArea were estimated to be higher by 33% and 27% in ballasted track and by 39% and 30% in concrete track than the dynamic factor derived from field measurement, respectively, which indicates that the dynamic factor currently in use can potentially lead to over-estimation in track design and maintenance. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Study on the Applicability of Dynamic Stability Evaluation Criteria by Comparison of Trackside Measurement Results of Different Track Structures
Appl. Sci. 2020, 10(22), 8245; https://doi.org/10.3390/app10228245 - 20 Nov 2020
Viewed by 273
Abstract
Countries such as Korea adopt design codes, evaluation criteria and specifications from standards originating abroad; this leads to a lack of distinction of the separate applications of dynamic stability evaluation parameters between various track structures of different track moduli. This paper discusses the [...] Read more.
Countries such as Korea adopt design codes, evaluation criteria and specifications from standards originating abroad; this leads to a lack of distinction of the separate applications of dynamic stability evaluation parameters between various track structures of different track moduli. This paper discusses the applicability of the dynamic stability evaluation method of railway track structures by assessing 10 different types of railway track sections of a newly constructed railway operation line (5 ballasted and 5 concrete type track structures) by field instrumentation testing. Parameters of track support stiffness (TSS), wheel load fluctuation, derailment coefficient, and rail displacement are measured. The respective results are first compared to the standard criteria (design specification) and comparisons between the different track types are presented as ratios. Findings show that while all of the tracks satisfy the design specification requirements, each track type measurement result varies by a noticeable degree, particularly when comparing between concrete and ballast type track structures. Results of the study demonstrate that using the same dynamic stability evaluation criteria can lead to an incorrect assessment of the track performance evaluation of track structure, and a separate evaluation parameter for ballasted and concrete track structures is required. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Improvement and In-Situ Application of an Evaluation Method of Ballasted-Track Condition Using Digital 2-D Image Analysis
Appl. Sci. 2020, 10(21), 7946; https://doi.org/10.3390/app10217946 - 09 Nov 2020
Viewed by 353
Abstract
The advancement in digital image analysis methods has led to the development of various techniques, i.e., quantification of ballast gravel abrasion. In this study, the recognition rate of gravel aggregates has been significantly increased by improving the image analysis methods. The correlation between [...] Read more.
The advancement in digital image analysis methods has led to the development of various techniques, i.e., quantification of ballast gravel abrasion. In this study, the recognition rate of gravel aggregates has been significantly increased by improving the image analysis methods. The correlation between the track quality index (TQI), which is the standard deviation of vertical track irregularity and represents the condition of a high-speed railway, and the number of maintenance works was analyzed by performing an image analysis on the samples collected from various locations of a high-speed railway. The results revealed that roundness has the highest correlation with the TQI, whereas sphericity has the highest correlation with the number of maintenance works. The ballast replacement would be performed to improve maintenance efficiency if the abrasion of the ballast aggregates becomes approximately 10%. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Arching Detection Method of Slab Track in High-Speed Railway Based on Track Geometry Data
Appl. Sci. 2020, 10(19), 6799; https://doi.org/10.3390/app10196799 - 28 Sep 2020
Viewed by 547
Abstract
During the long-term service of slab track, various external factors (such as complicated temperature) can result in a series of slab damages. Among them, slab arching changes the structural mechanical properties, deteriorates the track geometry conditions, and even threatens the operation of trains. [...] Read more.
During the long-term service of slab track, various external factors (such as complicated temperature) can result in a series of slab damages. Among them, slab arching changes the structural mechanical properties, deteriorates the track geometry conditions, and even threatens the operation of trains. Therefore, it is necessary to detect slab arching accurately to achieve effective maintenance. However, the current damage detection methods cannot satisfy high accuracy and low cost simultaneously, making it difficult to achieve large-scale and efficient arching detection. To this end, this paper proposed a vision-based arching detection method using track geometry data. The main works include: (1) data nonlinear deviation correction and arching characteristics analysis; (2) data conversion and augmentation; (3) design and experiments of convolutional neural network- based detection model. The results show that the proposed method can detect arching damages effectively, and the F1-score reaches 98.4%. By balancing the sample size of each pattern, the performance can be further improved. Moreover, the method outperforms the plain deep learning network. In practice, the proposed method can be employed to detect slab arching and help to make maintenance plans. The method can also be applied to the data-based detection of other structural damages and has broad prospects. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
A Method to Supervise the Effect on Railway Radio Transmission of Pulsed Disturbances Based on Joint Statistical Characteristics
Appl. Sci. 2020, 10(14), 4814; https://doi.org/10.3390/app10144814 - 13 Jul 2020
Cited by 1 | Viewed by 498
Abstract
Radiocommunication systems between train and trackside (RSTT) carry essential information for train operations between on-board radio equipment and the related radio infrastructure located along the trackside, such as the train control, voice dispatching, command, operational information as well as the monitoring data. In [...] Read more.
Radiocommunication systems between train and trackside (RSTT) carry essential information for train operations between on-board radio equipment and the related radio infrastructure located along the trackside, such as the train control, voice dispatching, command, operational information as well as the monitoring data. In a high-speed railway environment, the electromagnetic interference (EMI) has been a major threat to RSTT, and may result in critical security issues for railway transportation and even passengers. Given the complex scenario of the high-speed railway, it is significant to monitor the impact of disturbances in order to guarantee the quality of RSTT. On one hand, RSTT operate in a complex electromagnetic environment where transient disturbances coexist with permanent ones, and they both vary dramatically while the train is running. On the other hand, various radiocommunication technologies have been used for railway applications, featuring forward error-correction codes to resist EMI. Therefore, this paper puts forward a novel approach to evaluate the impact on radio transmission based on the joint statistical characteristics of time-varying EMI. This approach applies a dynamic effective signal-to-interference-plus-noise ratio mapping model to establish the relation between the block error performance of on-board radio and the joint statistical characteristics of disturbances with a mutual information-based metric. Simulations on radio transmission using Turbo coding and low-density-parity-check coding under various interferences indicate that this approach is effective to evaluate the degradation of transmission signal with forward error-correction coding due to EMI with different characteristics. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Ballasted Track Status Evaluation Based on Apparent Track Stiffness Index
Appl. Sci. 2020, 10(14), 4729; https://doi.org/10.3390/app10144729 - 09 Jul 2020
Viewed by 358
Abstract
Currently, maintenance work for ballasted track is performed based on the Track Quality Index (TQI) without a fundamental cause investigation for track irregularity. In this study, a new evaluation standard for ballasted track status is proposed to overcome the limitations of current maintenance [...] Read more.
Currently, maintenance work for ballasted track is performed based on the Track Quality Index (TQI) without a fundamental cause investigation for track irregularity. In this study, a new evaluation standard for ballasted track status is proposed to overcome the limitations of current maintenance work. The new evaluation standard is based on the stiffness index. The stiffness index is defined as the difference between the average and standard deviation of the apparent track stiffness determined by a light falling weight deflectometer (LFWD). After some field tests and analysis, it is shown that the stiffness index has a strong correlation not only with TQI but also with maintenance history. In verification results, the new evaluation standard estimated the ballasted track status quite well. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Determination of Necessary Subsidiary Track According to Train Operation Frequency in a Heterogeneous Train Pattern
Appl. Sci. 2020, 10(12), 4164; https://doi.org/10.3390/app10124164 - 17 Jun 2020
Viewed by 398
Abstract
In this study, a genetic algorithm was used to calculate the scheduled waiting time according to the train operation frequency of heterogeneous trains operating on one track. The acquired data were then used to determine the appropriate subsidiary track at which high-speed trains [...] Read more.
In this study, a genetic algorithm was used to calculate the scheduled waiting time according to the train operation frequency of heterogeneous trains operating on one track. The acquired data were then used to determine the appropriate subsidiary track at which high-speed trains can load or release cargo away from low-speed trains. A metaheuristic genetic algorithm was applied and implemented using Javascript/jQuery. Six cases were investigated, which provided values of subsidiary track that vary according to the operation frequencies of different types of trains, and solutions were derived through 100 simulations using a stochastic method. The analysis results showed that the train overtaking frequency was the highest at the third intermediate station within the simulation, suggesting that this particular station requires a subsidiary track, even if the operating frequency of each train differs across the entire track considered in this study. The results of this study are expected to facilitate objective and practical planning during railway construction. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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Open AccessArticle
Investigation on Interface Damage between Cement Concrete Base Plate and Asphalt Concrete Waterproofing Layer under Temperature Load in Ballastless Track
Appl. Sci. 2020, 10(8), 2654; https://doi.org/10.3390/app10082654 - 12 Apr 2020
Cited by 2 | Viewed by 586
Abstract
The interfacial bond between cement concrete base plate (CCBP) and asphalt concrete waterproofing layer (ACWL) is a weak portion in the newly developed Chinese high-speed railway ballastless track. The interface damage caused due to fluctuating temperature load and dynamic train load is one [...] Read more.
The interfacial bond between cement concrete base plate (CCBP) and asphalt concrete waterproofing layer (ACWL) is a weak portion in the newly developed Chinese high-speed railway ballastless track. The interface damage caused due to fluctuating temperature load and dynamic train load is one of the most critical problems in Northern China. This paper aims to investigate the interface damage evolution process under temperature load via experimental and simulation analysis. Full-scale transverse shear tests were performed to explore the interface bond-slip mode of the adjacent ACWL and CCBP. Then, a finite element model of a ballastless track structure was built and a cohesive zone model (CZM) was utilized to model the interface damage initiation, crack propagation, and delamination process under uniform/gradient temperature load. Furthermore, the dynamic response of the ballastless track where CCBP and ACWL were partly/totally debonded was investigated and compared with the perfectly bonded structure. The results demonstrate that bilinear CZM is capable of revealing the interface damage initiation, crack propagation, and delamination process under temperature load. The interface state between the adjacent CCBP and ACWL was greatly affected by temperature changes and the interface bonding state had a great impact on the dynamic response of ballastless track. Full article
(This article belongs to the Special Issue Monitoring and Maintenance Systems for Railway Infrastructure)
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