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Buildings are energy- and resource-hungry: their construction and use account for around 39% of global carbon dioxide emissions; they consume around 40% of all the energy produced; they are responsible for over 35% of the EU's total waste generation; and account for about 50% of all extracted (fossil) materials. Therefore, they present a significant challenge to meeting national and international Net Zero targets of reducing greenhouse emissions and fossil resource use. The CircularB Project, is at the heart of this issue, which will underpin synergies of multi-scale circular perspectives (from materials, to components, to assets and built environments), digital transformation solutions, data-driven and complexity science, stakeholder behavioral science, and interdisciplinary capabilities towards achievable, affordable and marketable circular solutions for both new and existing buildings, for sustainable urban design, and for circular built environments across Europe. This paper contributes to the project by deriving new insights into the stakeholders' influences, inter-relationships, and obstacles in the implementation of circular economy concepts on existing building stocks in Europe, which represent over 90% of whole building assets. In order to identify and derive the insights, our study is rigorously based on (i) a robust critical literature review of key documentations such as articles, standards, policy reports, strategic roadmaps and white papers; and (ii) interviews with relevant stakeholders and decision makers. Uniquely, our work spans across all scales of CE implementation from materials, to products and components, to existing building stocks, and to living built environments. The findings point out the current challenges and obstacles required to be tackled. Inadequacies of financial incentives and governmental enforcement (via policy, legislation, or directive) are commonly found to be the most critical obstacles found throughout Europe. Circular economy is the global challenge and not just a single country can resolve the climate issue without the cooperation of other countries. The insights thus highlight the essential need for harmonized actions and tactical/pragmatic policies promoted and regulated by the European Commission, national and local governments who can dominate the influence, promote inter-relationship, and overcome the barriers towards circular economy much more effectively. [ABSTRACT FROM AUTHOR]

• A new damage quantification based on peridynamic theory has been established. • This new approach tackles the complex crack initiation plane, which is unsolved. • The new technique has been validated by experimental case studies. • The predictions exhibit very good agreements with experiments. • Crack propagation patterns can be accurately predicted using this new approach. This paper proposes a novel approach to evaluate the damage in Peridynamic simulations to identify the crack initiation and propagation, based on the physical meaning of the bond network. The most commonly used criterion to assess the damage in Peridynamic simulations is the nodal damage value, a ratio of the broken bonds to number of unbroken bonds for each point. There is no consensus on the magnitude of nodal damage value within the literature. In most cases, the assessment is conducted visually via damage contours. Rarely, researchers calculate nodal damage value by counting the bonds that pass through a crack plane and must be broken to initiate a crack. Despite being widely-used, the application of nodal damage value is questionable since it neglects the likelihood of broken bonds that are irrelevant to a crack. In other words, the applied value of the nodal damage value might not give the information about the crack whether it emerges or not. This paper shows the influence of the nodal damage value on damage assessments and compares the proposed method with the nodal damage value in different scenarios. The results exhibit that the proposed method is robust, effective, and more importantly provides a single outcome for Peridynamic simulations. [ABSTRACT FROM AUTHOR]

As the key safety-critical component of a bridge support system, bridge bearings are extensively used to accommodate, balance, and transfer differential displacements and loads between the superstructure and substructure of a bridge during operations. Several studies have been conducted to obtain dynamic modal parameters of traditional bridge bearings only in perfectly dry environments. However, in extreme weather conditions (e.g., heavy rain, flash floods, etc.), water can ingress and change the bearings' properties. In this study, novel 3D-printed porous bridge bearings (3DPPBBs) have been fabricated by Fused Deposition Modeling (FDM) with thermoplastic polyurethane (TPU) filaments. This study is the first to determine the influences of flood conditions on their dynamic properties, which has never been done before. An idealised single degree of freedom (ISDOF) for these novel bearings is considered for the non-destructive field-testing technique of the critical bridge component. A series of experimental tests have been performed under several conditions of flooding levels. The new results unprecedentedly indicate that relatively higher dynamic damping ratios can be found with the increasing flood levels. In contrast, the natural frequencies and dynamic stiffness decrease with the same conditions. Novel insights are essential for bridge engineers to assess and monitor bridge vibrations exposed to extreme weather conditions. [ABSTRACT FROM AUTHOR]

Railway maintenance is a complex and complicated task in the railway industry due to the number of its components and relationships. Ineffective railway maintenance results in excess cost, defective railway structure and components, longer possession time, poorer safety, and lower passenger comfort. Of the three main maintenance approaches, predictive maintenance is the trendy one, and is proven that it provides the highest efficiency. However, the implementation of predictive maintenance for the railway industry cannot be done without an efficient tool. Normally, railway maintenance is corrective when some things fail or preventive when maintenance is routine. A novel approach using an integration between deep reinforcement learning and digital twin is proposed in this study to improve the efficiency of railway maintenance which other techniques such as supervised and unsupervised learning cannot provide. In the study, Advantage Actor Critic (A2C) is used to develop a reinforcement learning model and agent to fulfill the need of the study. Real-world field data over four years and 30 km. is obtained and applied for developing the reinforcement learning model. Track geometry parameters, railway component defects, and maintenance activities are used as parameters to develop the reinforcement learning model. Rewards (or penalties) are calculated based on maintenance costs and occurring defects. The new breakthrough exhibits that using reinforcement learning integrated with digital twin can reduce maintenance activities by 21% and reduce the occurring defects by 68%. Novelties of the study are the use of A2C which is faster and provides better results than other traditional techniques such as Deep Q-learning (DQN), each track geometry parameter is considered without combining into a track quality index, filed data are used to develop the reinforcement learning model, and seven independent actions are included in the reinforcement learning model. This study is the world's first to contribute a new guideline for applying reinforcement learning and digital twins to improve the efficiency of railway maintenance, reduce the number of defects, reduce the maintenance cost, reduce the possession time for railway maintenance, improve the overall safety of the railway operation, and improve the passenger comfort which can be seen from its results. [ABSTRACT FROM AUTHOR]

Unplanned track inspections can be a direct consequence of any disruption to the operation of on-board track geometry monitoring activities. A novel response strategy to enhance the value of the information for supplementary track measurements is thus established to construct a data generation model. In this model, artificial (synthetic) data is assigned on each measurement point along the affected track segment over a short period of time. To effectively generate artificial track measurement data, this study proposes a NARX (nonlinear autoregressive with exogenous variables) model, which incorporates short-range memory dependencies in the dependent variable and integrates interdependent effects from external factors. Nonlinearities in the proposed model have been determined using an artificial neural network that allowed fast computation of a mapping function in line with the needs of effective disruption management. The risk of over fitting the data generation model, which reflected its generalisation ability, has been effectively managed through risk aversion concept. For the model evaluation, the deviation of track longitudinal level has been taken as a case study, predicted using its degradation rate and track alignment and gauge as exogenous variables. Simulation results on two datasets that are statistically different showed that the data generation model for disrupted track measurements is reliable, accurate, and easy-to-use. This novel model is an essential breakthrough in railway track integrity prediction and resilient operation management. [ABSTRACT FROM AUTHOR]

Most of the Artificial Intelligence (AI) models currently used in energy forecasting are traditional and deterministic. Recently, a novel deep learning paradigm, called 'transformer', has been developed, which adopts the mechanism of self-attention. Transformers are designed to better process and predict sequential data sets (i.e., historical time records) as well as to track any relationship in the sequential data. So far, a few transformer-based applications have been established, but no industry-scale application exists to build energy forecasts. Accordingly, this study is the world's first to establish a transformer-based model to estimate the energy consumption of a real-scale university library and benchmark with a baseline model (Support Vector Regression) SVR. With a large dataset from 1 September 2017 to 13 November 2021 with 30 min granularity, the results using four historical electricity readings to estimate one future reading demonstrate that the SVR (an R2 of 0.92) presents superior performance than the transformer-based model (an R2 of 0.82). Across the sensitivity analysis, the SVR model is more sensitive to the input close to the output. These findings provide new insights into the research area of energy forecasting in either a specific building or a building cluster in a city. The influences of the number of inputs and outputs related to the transformer-based model will be investigated in the future. [ABSTRACT FROM AUTHOR]

Railway track maintenance plays an important role in enabling safe, reliable, and seamless train operations and passenger comfort. Due to the increasing rail transportation, rolling stocks tend to run faster and the load tends to increase continuously. As a result, the track deteriorates quicker, and maintenance needs to be performed more frequently. However, more frequent maintenance activities do not guarantee a better overall performance of the railway system. It is crucial for rail infrastructure managers to optimize predictive and preventative maintenance. This study is the world's first to develop deep machine learning models using three-dimensional recurrent neural network-based co-simulation models to predict track geometry parameters in the next year. Different recurrent neural network-based techniques are used to develop predictive models. In addition, a building information modeling (BIM) model is developed to integrate and cross-functionally co-simulate the track geometry measurement with the prediction for predictive and preventative maintenance purposes. From the study, the developed BIM models can be used to exchange information for predictive maintenance. Machine learning models provide the average R2 of 0.95 and the average mean absolute error of 0.56 mm. The insightful breakthrough demonstrates the potential of machine learning and BIM for predictive maintenance, which can promote the safety and cost effectiveness of railway maintenance. [ABSTRACT FROM AUTHOR]

Innovative digital twins (DTs) that allow engineers to visualise, share information, and monitor the condition during operation is necessary to optimise railway construction and maintenance. Building Information Modelling (BIM) is an approach for creating and managing an inventive 3D model simulating digital information that is useful to project management, monitoring and operation of a specific asset during the whole life cycle assessment (LCA). BIM application can help to provide an efficient cost management and time schedule and reduce the project delivery time throughout the whole life cycle of the project. In this study, an innovative DT has been developed using BIM integration through a life cycle analysis. Minnamurra Railway Bridge (MRB), Australia, has been chosen as a real-world use case to demonstrate the extended application of BIM (i.e., the DT) to enhance the operation, maintenance and asset management to improve the sustainability and resilience of the railway bridge. Moreover, the DT has been exploited to determine GHG emissions and cost consumption through the integration of BIM. This study demonstrates the feasibility of DT technology for railway maintenance and resilience optimisation. It also generates a virtual collaboration for co-simulations and co-creation of values across stakeholders participating in construction, operation and maintenance, and enhancing a reduction in costs and GHG emission. [ABSTRACT FROM AUTHOR]

With an emphasis on the integrated deterioration of railway track geometry and components, a new hybrid numerical-analytical method is proposed for the predictive analysis of track geometrical vertical levelling loss (VLL). In contrast to previous studies showing a dependency on the number of cycles, this research unprecedentedly incorporates the influence of operational, vehicle and track conditions. The numerical models are carried out using an explicit finite element (FE) package under cyclic loadings, and then, their outcomes are iteratively regressed by an analytical logarithmic function that accumulates permanent deformations in order to quantify VLL over a long term. The results are first compared with other previous studies, indicating a very good agreement with them. Then, field measurements have been used to further verify the results. In this study, parametric simulations are performed varying three key parameters: axle load, train velocity and ballast tangent stiffness. The parametric studies exhibit that the rate of VLL raises about 50% if the axle load increases only from 30 ton to 40 ton for a freight train running at 70 km/h on a stiffer ballast track. In contrast, for a 25-tonnes-axle-load train running from 60 km/h to 100 km/h on a similar track, the vertical levelling degradation reduces by approximately 20%. The main findings suggest that higher axle loads contribute significantly to the VLL due higher contact forces and, on the other hand, a lower train speed does not necessarily imply a low rate of VLL since the influence of train velocities on track geometry (VLL) is associated with the natural frequencies (or wavelengths) of the ballasted railway track. The insight demonstrates that the load frequencies play a key role on the deterioration of VLL. [ABSTRACT FROM AUTHOR]

Investigating the condition of rail track components is important for track maintenance and developing a greater understanding of track design. Railway inspection can be destructive and non-destructive approaches. In the railway industry, the non-destructive approaches are preferred because they retain the track in operation thus significantly reducing the cost of fault testing. One of the non-destructive approaches is using machine learning which is applied in this study. Field measurements and advanced analysis of results are used to extract track properties. This study creates, tunes and examines the validity of different machine learning techniques. The aim is to extract the dynamic track properties from the in-field measurements without needing the intermediary steps, saving both time and effort. Contributions of this study demonstrate that machine learning techniques have the potential to save cost and time for railway inspection. Moreover, the accuracy is satisfied. The following models are produced: Linear Regression, K-Nearest Neighbors, Gradient Boosting and a Convolutional Neural Network. We observe the limitations of linear regression and tune the remainder, producing three models with low errors. [ABSTRACT FROM AUTHOR]

Railway track health monitoring and maintenance are crucial stages in railway asset management, aiming to enhance the train operation quality and service life. For this aim, various inspection means (using diverse non-destructive testing techniques) have been applied, however, these means are mostly not able to monitor whole railway track network or track underlying layers (e.g., ballast and subgrade). The use of remote sensing techniques, such as Interferometric Synthetic Aperture Radar (InSAR), can expedite the defect diagnosis process for railway tracks, elevating the scope of health monitoring to a network-wide level. The Ground Penetrating Radar (GPR) has emerged as a particularly reliable method, especially for detecting structural deficiencies in underlying layers. As a result, combining the two distinct non-destructive testing techniques – GPR and InSAR – presents a promising strategy for efficient railway asset management. Recognizing the significance of embracing newer and more advanced monitoring strategies, this paper reviews the fusion of GPR and InSAR methodologies, and explores the potential integration of machine learning models to develop a predictive health monitoring and condition-based maintenance approach for railway tracks. • A review of InSAR/GPR with potential fusion for railway monitoring was discussed. • A general framework for fusion of InSAR/GPR data and machine learning integration was proposed. • Predictive strategy based on fusion of characterized techniques for railway health monitoring/maintenance plan was focused. • Future research directions are recommended based on the review of literature and discussion of technology. [ABSTRACT FROM AUTHOR]

This paper investigates the possibility for implementing machine learning-aided prediction in analyzing the buckling phenomena of ballasted railway tracks induced by extreme temperature. In this study, artificial neural networks (ANNs) have been developed to identify the relationship between various ballasted track conditions and outputs, namely safe temperature and buckling temperature. The variables included in the objective function of the optimization problems are the lateral resistance of ballasted track provided by ballast-sleeper interaction, torsional resistance provided by fastening systems, and misalignment of the track. Due to its complexity in parameter combinations, the objective of this study is to create predictive models with the aim of minimizing the usage of scarce resources. Thus, this paper is the first to develop a novel machine learning-aided prediction of railway track buckling due to extreme temperature. Comprehensively, all 353 datasets of the safe and buckling temperatures derived from previous finite element (FE) simulation results have been collected and trained. Note that the mean squared error (MSE) and the coefficient of determination ( R 2) are considered to quantify the performance of the ANN architectures. The optimal ANN architecture with a very high rate of accuracy has been determined and highlighted. Thus, the suggested neural network model can be applied conveniently to help estimate safe and buckling temperatures of the complex track models in order to improve track conditions and thus prevent track buckling in summer. [ABSTRACT FROM AUTHOR]

Railway sleepers are safety–critical components of a railway structure. They support ballasted track superstructure and are a critical factor in track geometry and track components' deterioration. Unsupported sleepers are a common issue incurred after tracks have been utilized. When unsupported sleepers are present, they cause differential settlements of track superstructures, additional dynamic loading, and excessive train-track vibrations which affect passenger comfort, safety, and maintenance cost. This study is the world's first to develop new machine learning models to prognose and better diagnose defect severities of unsupported sleepers aligned with practical track inspection guidelines. Data used to develop machine learning models are based on a verified finite element model with actual field measurements, enabling unbiased full data ranges that govern all defect conditions. Different conditions of unsupported sleepers can be explored by varying locations of unsupported sleepers and the number of unsupported sleepers. Also, other operational parameters can be addressed such as speeds of rolling stock, the roughness of rail surface, and vertical stiffness of wheel-rail contact. In total, 2016 data sets have been obtained. Axle box accelerations are adopted as key indicators for machine learning models. Machine learning techniques used in the study are the convolutional neural network, recurrent neural network, ResNet, and fully convolutional neural network. Data fusion and assimilation have been conducted since the data points are dependent on the train speeds. Our new results reveal a breakthrough essential for real-world applications that the convolutional neural network model provides the best accuracy in both unsupported sleeper prognostics and severity identification. The accuracies of detection and severity identification are 99.34% and 97.02% respectively. [ABSTRACT FROM AUTHOR]

In 2011, the percentage of the American population affected by Noise Induced Hearing Loss (NIHL) was 15.3%. Unlike most forms of hearing loss, this can be prevented by limiting exposure to certain magnitudes of noises for varying amounts of time. The present study, using six calibrated smartphones, aims to assess the sound given off from dropping free weights in the gym, at the University of Birmingham, which can be contributing to NIHL. A relationship between drop weight and vibration is also constructed. For vibration, it is found that vibration level (m/s2) increases with the drop weight, whereas the average noise level for each drop weight only varies by a range of 4.4 dB between 102.7 and 98.3 dB. Note that all the sound levels recorded are over 85 dB, which is the range where NIHL can be contributed to. This study reminds us that measures need to be taken to reduce the sound level from the drops of loaded barbells in any sports and fitness centers. [ABSTRACT FROM AUTHOR]

• Schwarz Primitive structures are fabricated using stereolithography technology. • 3D printed metamaterials are robustly tested under axial load conditions. • It is the first time that nonlinear behaviours of complex porous composite metamaterials has been benchmarked. • The discrete element method is adopted to simulate the Schwarz Primitive metamaterials validated by experimental tests. • New insights into crack patterns of composite metamaterials are the precursor to engineering applications. This study delves into the axial responses of Schwarz Primitive (SP) structures. Emphasising on bearing capacity, force distribution, cracking phenomena, load-displacement curve and energy absorption. Discrete element method (DEM) is adopted to analyse the axial load-bearing behaviour and fracture mechanics of Main SP and Secondary SP structures under various unit cell configurations after validated by experimental tests. The results indicates that despite sharing the same 1/8th cell structure, the axially-loaded behaviours of the Main SP and Secondary SP structures are not identical, particularly in scenarios involving a large unit cell size and a small number of unit cells. The Main SP structures display an axial load-bearing behaviour that is largely unaffected by variations in the number of unit cells along the x and y axes, while Secondary SP structures show a more pronounced improvement in average strength and energy absorption capacity when the number of unit cells increases. Main SP structures offer superior axial load-bearing capabilities and energy absorption efficiency, which is a significant consideration for their application in scenarios demanding high structural integrity. This distinction underlines the importance of tailored design and selection of SP configurations based on specific engineering requirements. [ABSTRACT FROM AUTHOR]

This paper adopts both explicit and implicit finite element methods in a specialist package LS-DYNA to investigate the nonlinear, dynamic response of a long span shell roof structure when subjected to blast loading. Parametric studies have been carried out on blast loaded laminated glass plates with reference to experimental results obtained by European researchers. A case study that has been chosen is a light rail station in The Netherlands called The Erasmusline. Following the detonation of 15 kg TNT charge, explicit analysis showed breakage surrounding the rigid supports along the edge beam where modal vibrations are restrained. An implicit analysis has confirmed the resonances in global eigen-frequencies where most blast damage is localized around the roof canopy hence producing cracking and potential glass detachment from the panels without full structural demolition. This insight from this study will inform structural engineers about the potential modes of failure and preventative strategies to minimize further secondary losses of life or assets from a terrorist attack. [ABSTRACT FROM AUTHOR]

Steel–concrete composite railway track slabs are a financially viable alternative for the modular construction of railway slab tracks and for the replacement of resilient timber transoms on railway bridges, and design and experiments have been carried out to investigate their technical feasibility. Extended findings based on dynamic eigenvalue analyses of a precast steel–concrete composite slab panel for a track support structure are presented in this paper. The natural frequencies of the railway composite slab were investigated using the finite-element package Abaqus. Dynamic eigenmodes were then extracted using the Lanczos method. Modal cross-over phenomena were clearly observed when the design mass of the track slab was changed. This paper highlights the unprecedented dynamic mode coupling effects on composite track slabs over a railway bridge. This insight can be used to improve practical noise- and vibration-control technologies through composite material design, resulting in quieter railway track slabs. [ABSTRACT FROM AUTHOR]

The main functions of the sleepers in ballasted tracks include transferring loads, securing rail gauge and maintaining railway track geometry. Sleepers can be manufactured using timber, concrete, steel or other engineered materials, but concrete is most commonly used around the world. There are a number of researches on the impact load characteristics and the ultimate load carrying capacity of prestressed concrete sleepers, but research on the fatigue life of prestressed concrete sleepers is very limited. A prestressed concrete sleeper's fatigue damage is mainly due to the repeated loads derived from dynamic wheel-rail interactions, especially when either wheel or rail irregularity is present. Fatigue failure is thus a time-dependent limited state where a concrete sleeper accumulates damage to a failure point over its service life. Concrete sleepers could usually suffer from the dynamic fatigue loading spectra throughout their whole lives, and simultaneously, both static and dynamic load-carrying capacities of concrete sleepers degrades over time. Therefore, a fatigue life assessment is an important and complicated research frontier. Field loading conditions, material time-dependent and dynamic properties, and the dynamic bending moments of prestressed concrete sleepers are quantitatively analysed in this study. This paper also presents an updated fatigue life assessment method for concrete sleepers, and provides a case study based on actual field loading conditions and the time-dependent behaviour of materials. The new insights obtained from this study will improve concrete sleeper maintenance and inspection criteria, and provide a new reference for a rational dynamic design principle of railway concrete sleepers and bearers. • Life cycle modelling of railway sleepers is firstly presented. • Track loading annals are analysed from the fields. • Fatigue life assessment model of railway concrete sleepers has been validated with experimental data. • It is the first time that the endurance of railway sleepers is identified using the actual annual loading conditions. • Time-dependent effects play a significant role on the remaining fatigue life of concrete sleepers. [ABSTRACT FROM AUTHOR]

Each day tens of turnout-related derailment occur across the world. Not only is the prediction of them quite complex and difficult, but this also requires a comprehensive range of applications, and managing a well-designed geographic information system. With the advent of Geographic Information Systems (GIS), and computers-aided solutions, the last two decades have witnessed considerable advances in the field of derailment prediction. Mathematical models with many assumptions and simulations based on fixed algorithms were also introduced to estimate derailment rates. While the former requires a costly investment of time and energy to try and find the most fitting mathematical solution, the latter is sometimes a high hurdle for analysists since the availability and accessibility of geospatial data are limited, in general. As train safety and risk analysis rely on accurate assessment of derailment likelihood, a guide for transportation research is needed to show how each technique can approximate the number of observed derailments. In this study, a new stochastic mathematical prediction model has been established on the basis of a hierarchical Bayesian model (HBM), which can better address unique exposure indicators in segmented large-scale regions. Integration of multiple specialized packages, namely, MATLAB for image processing, R for statistical analysis, and ArcGIS for displaying and manipulating geospatial data, are adopted to unleash complex solutions that will practically benefit the rail industry and transportation researchers. • All estimates seem to be incapable of calculating an estimate for a low number of derailments. • the assumptions seldomly yield a precise estimate of the derailment rates under any uncertainty • Some assumptions which relied on turnout counts, are observed to deviate from the observations • the assumptions regarding turnout counts are a weak spot even when being generated mathematically on the basis of a concrete belief. [ABSTRACT FROM AUTHOR]

Railway turnouts or so-called 'switches and crossings' are complex systems by nature of design and construction. Railway turnouts are used to change direction of trains from one to another. They require high-quality construction and maintenance, in order to minimise rapid degradation and component failures that could result in train derailments. Due to the complexity of railway turnouts, the efficiency and effectiveness of maintenance can be improved by integrating existing practice by Building Information Modelling (BIM). This research establishes and analyses the world's first 6D BIM for life cycle management of a railway turnout system. The BIM (Level 3) has integrated 6-dimensions of field data information based on Revit-2018 and Navisworks-2018 platforms. The digital twins of a railway turnout in 3D embrace time schedule, costs and sustainability across the whole life cycle. The use of BIM for railway turnout systems has the potential to improve the overall information flow of the turnout planning and design, manufacturing pre-assembly and logistic, construction and installation, operation and management and demolition, thereby achieving better project performance and quality. Based on integrated information of railway turnout system, the 6D BIM has the ability to assess on economic, management and sustainability, and achieve a balance among them. This is the word first to demonstrate that BIM can fully deliver its essential benefits by information sharing, easing technical communication, improving design quality, reducing of design errors, accelerating implementation, speeding up work, shortening construction duration, reducing construction costs, enhancing carbon efficiency, supporting project management, and providing its owners with higher operational efficiency over the railway turnout system life-cycle. The results reveal that embodied material emission is the main contributor towards carbon footprint, especially produced during the manufacturing stage. The reconstruction stage contributes the most expensive phase of life cycle. The insight will significantly benefit the co-value creation among engineers, project managers, technicians, and senior management team. • Digital twin or BIM (Level 3) of railway switches and crossings is established. • It is the first to highlight sustainability-based life cycle management of railway turnout systems. • The life cycle analyses consider both cost and environmental impacts using field data, design and case studies. • The outcomes highlight best practices for sustainable and cleaner solutions for life cycle management of turnout systems. • The insight will benefit the co-value creation among engineers, project managers, technicians, and senior management team. [ABSTRACT FROM AUTHOR]

In recent years, significant research has been conducted to explore the use of 3D triply periodic minimal surface (TPMS) structures for their exceptional vibrational damping properties and their ability to provide a continuous, smooth surface. The emergence of 3D printing has enabled the application of TPMS structures in fields such as medicine and aviation. In civil engineering, the compressive capacity of structures is a fundamental parameter in structural design. To evaluate the potential of porous TPMS structures in civil engineering, we have designed and manufactured four types of Skeletal-TPMS units using Stereolithography (SLA) technology. Axially loaded tests and nonlinear finite element method (NFEM) simulations have been performed to investigate the compressive strength and stiffness of the units. Our findings indicate that compared to solid blocks, the compressive strength of Skeletal-TPMS units decreases by 71.3% to 82.6%, and the stiffness decreases by 64.9% to 79.2%. The Skeletal-SP units show better compressive resistance than Skeletal-IWP units. This study provides new valuable insights for structural design and applications using TPMS structures in civil engineering. [ABSTRACT FROM AUTHOR]

On curved railway tracks, wheel/rail interface can usually cause a traveling source of sound and vibration, which constitutes high-pitch or tonal noise pollution causing considerable concern to rail asset owners, commuters and people living or working along the railway corridor. The sound and vibration can be in various forms and spectra. The undesirable tonal sound on curves caused by excessive lateral wheel/rail dynamics in resonance with falling friction states are often called 'squeal noises'. This paper evaluates the transient effect of curve radii on the possible occurrence of lateral track resonances, which is a principal cause of dynamic wheel/rail mode coupling that could trigger 'curve squeal'. This study is devoted to systems thinking approach and better insight into dynamic phenomena of railway tracks that could resolve the railway curve noise problems. Curved track models in three-dimensional space have been developed using a finite element package, STRAND7. The dynamic responses of curved track have been simulated by applying a moving train load. The transient loading model of a common wheel/rail slip has been adopted. The simulations of railway tracks with different curve radii have been carried out to develop state-of-the-art understanding of lateral track dynamics, including rail dynamics, cant dynamics and overall track responses. Parametric studies have been conducted to evaluate lateral displacements, velocities and accelerations of rail over sleeper and rail at midspan, both in static and dynamic conditions. The study firstly reveals that the lateral resonance of tangent tracks is relatively rare and the mode coupling behavior is unlikely to occur on moderately curved tracks. The lateral vibration responses have been presented in terms of time histories and spectro-temporal responses (also called "Spectogram"). The dynamic lateral responses of the track are found to be sensitive to the change of curved radii. The resonance peak in the lateral direction is related to the agreement of corresponding natural frequencies of rail and the vibration excitation frequencies under an individual rolling velocity. The outcome of this study establishes new insight into the dominant influences of different track parameters to track lateral dynamic behaviors. [ABSTRACT FROM AUTHOR]

Abstract According to a large number of end-of-life rolling stocks were left over landfill, appropriate waste management should start by properly understanding the components of rolling stocks to determine their remaining potential. This paper evaluates efficient and feasible approaches to recovering and recycling wasted rolling stocks. The emphasis is placed on three broad train types, consisting of freight train, passenger train, and High-Speed Rail (HSR). In this article, all compositions of the three types of rolling stock are studied, with the results of the recyclability and recoverability rates being used to inform their productive treatment at the end-of-life. The distinctive point of this research is an analysis of compositions, materials, and the percentage of value adopted from the end-of-life rolling stocks. With respect to find out the recyclability (R cyc) and recoverability (R cov) rates on end-of-life rolling stock, the equations are adopted from ISO 22,628:2002 document to estimate the feasibility and suitability of each component on the rolling stock for taking advantage from unused parts. By comparing the R cyc and R cov rates among three types of rolling stock at the end-of-life stage, the highest value of R cyc showed at 92.8% from freight train where the highest value of R cov represented at 12.5% from HSR. It was found that those rates relate to the main components on rolling stock, which contained diversely characteristic to be reusable, recyclable or recoverable materials. Finally, the two key recommendations for further design on rolling stocks are provided regarding the proper selection of materials and the method to enhance efficiency of recycling and recovering process. [ABSTRACT FROM AUTHOR]

Abstract Since multiple failure events associated with derailments could not be identified and derailment probability could not be reached quantitatively by event tree and fault tree analysis for safety assessment in railway systems, applications of Bayesian network (BN) were introduced over the last few years. The applications were often aimed at understanding safety and reliability of railway systems through various basic principles and unique inference algorithms focusing on particular railway infrastructures. One of the most critical engineering infrastructure, railway turnouts (RTs) have been investigated and analysed critically in order to develop a new BN-based model with unique algorithm. This unprecedented study reveals the causal relations between primary causes and the subsystem failures, resulting in derailment, as a result of extreme weather-related conditions. In addition, the model, which is designed for rare events, has been proposed to identify the probability and underlying root cause of derailment. Consequently, it is expected that various weather-related causes of derailment at RTs, one such undesirable event, which can result, albeit rarely, damaging rolling stock, railway infrastructure and disrupting service, and having the potential to cause casualties and even loss of life, are identified to allow for smooth railway operation by rail industry itself. The insight into this weather-derailment will help the industry to better manage railway operation under climate uncertainty. [ABSTRACT FROM AUTHOR]

Highlights • 3D FEMs have been developed and rigorously validated. • Full-scale tests prestressed concrete sleepers with holes and web openings are conducted. • It is the word first to identify damages and failure modes of the sleepers with holes and web openings. • Novel insights into the behaviours of the sleepers with holes and web openings exposed to impact loading are highlighted. • Two advanced material modelling techniques are exercised and benchmarked. • Brittle cracking model provides better damage predictions than Damage Plasticity Model. • Holes and web openings induce shear failure of the sleepers under impact loading. Abstract Prestressed concrete sleepers are essential to the structural integrity of railway track structures, redistributing wheel loads from the rails to underlying ballast bed while securing rail gauges for safe train traffics. In practice, drilled holes or web openings are usually generated ad hoc in sleepers to enable signalling equipment and cables at a construction site. These holes and web openings could however affect the structural integrity of sleepers, especially when they are exposed to impact loading. In fact, statistically, 15–25% of dynamic loading conditions are of transience and high-intensity by the nature of wheel-rail interaction over irregularities. This study is thus the world first to rigorously investigate the impact behaviours of railway sleepers with hole and web openings, which is critical to railway safety and reliability. In this study, three-dimensional finite element modelling using ABAQUS Explicit is used to comprehensively design and analyse the behaviour of prestressed concrete sleepers with various types of holes and web openings upon impact loading. Two different modelling techniques including concrete damaged plasticity model and brittle cracking model are also exercised to aid in this study. The results obtained show that the brittle cracking model provides better damage results as it can illustrate crack propagation very well until reaching the failure mode under impact loading. The findings illustrate a pathway to use brittle cracking model instead of concrete damaged plasticity model for dynamic impact analysis. Moreover, the outcome of this study will provide a better and new insight into the influences of holes and web openings on sleepers' failure modes under impact loading so that appropriate guidance can be proposed to rail and track engineers in order to generate holes and web openings ad hoc in prestressed concrete sleepers without compromising their structural performance. [ABSTRACT FROM AUTHOR]

Each year, there can be three to six millions of service train axles running over an open plain track. In fact, these trains could impose a variety of dynamic loading conditions depending on the wheel and rail maintenance levels. Inevitably, the risk of high-intensity dynamic loading conditions by wheel-rail interactions due to wheel or rail irregularity cannot be disregarded. Imperfection of rail tracks could lead directly to the exceedance of permissible stress of a track component and later amplify rapid track deterioration rates causing cracking in sleepers and failure of track substructure. Practical railway track irregularities can be typically classified into short wave length (high frequency) and long wave length (low frequency) defects, of which previous researchers had studied each in isolation. This paper is the first to study the influence on railway track inspection and maintenance priorities caused by the coupling of wave lengths between dipped rail joint and differential track settlements. To study the dynamic coupling effects, P1 and P2 forces are evaluated at the track irregularity together with rail/sleeper contact force, ballast pressure and bending moments of sleepers using dynamic multi-body simulation approach. It is found that some patterns of coupling irregularity could cause a significant reduction in dynamic impact factors whilst some are associated with an increase in the wheel/rail impact force. The insight has then been integrated to establish track performance indicators that are paramount for prioritising track inspection and maintenance. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The deflections of the submerged specimens are less than those in dry condition. • The dynamic and impact stiffness of the material in wet condition tends to be very high. • The dynamic damping tends to be lower in dry condition. • The closed cell polymeric foam materials can be applied as under ballast mats (UBM) in railway tracks. • The materials fit really well as a soft to medium UBMs. Abstract Polymeric materials have been used as critical components in a wide range of engineering structures in built environments. The superior characteristics of polymeric materials have led to various applications such as energy absorber during shock or impact events, lightweight structures, and thermal insulation. The key benefit is derived from relatively lower weight and density in comparison with other materials. The emphasis of this study is placed on closed-cell polymeric material, which is flexible and can potentially be manufactured as a rubber mat for railway track applications. A critical literature review reveals that the dynamic behavior of closed-cell polymeric material has not been fully investigated, especially when the materials are usually exposed to water. We are the first to present the wet/dry influences on the characteristics of closed cell cross-linked polyethylene foam under static, dynamic and shock loads. In our study, the water absorption and swelling of the materials are measured after 24 h of immersion in de-ionized water. Static, dynamic, and impact loading are applied to closed-cell polymeric materials on both wet and dry states. The behaviors and responses of the materials can inform whether or not a closed-cell polymeric material can be used as under ballast mats and under sleeper pads in railway tracks under operational environments. Based on our results, it is found that this closed-cell-polymeric material is not suitable for use as under sleeper pads. However, they have reasonably strong potential for use as under ballast mats under various rail operational parameters. [ABSTRACT FROM AUTHOR]

At present, railway infrastructure experiences harsh environments and aggressive loading conditions from increased traffic and load demands. Ground borne vibration has become one of these environmental challenges. Overhead line equipment (OHLE) provides electric power to the train and is, for one or two tracks, normally supported by cantilever masts. A cantilever mast, which is made of H-section steel, is slender and has a poor dynamic behaviour by nature. It can be seen from the literature that ground borne vibrations cause annoyance to people in surrounding areas especially in buildings. Nonetheless, mast structures, which are located nearest and alongside the railway track, have not been fully studied in terms of their dynamic behaviour. This paper presents the effects of ground borne vibrations generated by high speed trains on cantilever masts and contact wire located alongside railway tracks. Ground borne vibration velocities at various train speeds, from 100 km/h to 300 km/h, are considered based on the consideration of semi-empirical models for predicting low frequency vibration on ground. A three-dimensional mast structure with varying soil stiffness is made using a finite element model. The displacement measured is located at the end of cantilever mast which is the position of contact wire. The construction tolerance of contact stagger is used as an allowable movement of contact wire in transverse direction. The results show that the effect of vibration velocity from train on the transverse direction of mast structure is greater than that on the longitudinal direction. Moreover, the results obtained indicate that the ground bourn vibrations caused by high speed train are not strong enough to cause damage to the contact wire. The outcome of this study will help engineers improve the design standard of cantilever mast considering the effect of ground borne vibration as preliminary parameter for construction tolerances. [ABSTRACT FROM AUTHOR]

This paper investigates novel dynamic phenomena of interspersed railway tracks. The interspersed method is commonly carried out by spot-replacing old timber sleepers with new concrete sleepers. Although this interspersed approach provides a short-term solution, such method has a negative effect on the long-term performance of railway tracks. It is evident that the performance of interspersed tracks can quickly deteriorate after some years. As a result, this paper is the first to evaluate dynamic responses of the interspersed track caused by a moving train load in order to understand the root cause of swift track deterioration. Interspersed track models in three-dimensional space have been developed using a finite element package, STRAND7. The model was validated earlier with experimental results. Parametric studies have been conducted to evaluate dynamic responses of the interspersed railway tracks, including dynamic displacement, frontal uplift, rear uplift and accelerations of rail over sleeper, rail at midspan, sleeper at rail seat, and sleeper at midspan. Dynamic amplification phenomena are highlighted as they convey a new insight into dynamic phenomena identifying the real source of track deterioration. [ABSTRACT FROM AUTHOR]

Academics are by far more responsive to social, economic and technological changes and therefore academic identity must be resilient and flexible in order to fully engage with diverse and numerous purposes of academic institutions. Considering the fierce competition in the UK higher education sector, the demand for an academic curriculum to be globally relevant is greater than ever. In this paper, new challenges within the British higher education setting in globally competitive environment are discussed. The railway engineering curriculum within civil engineering programme at the University of Birmingham (accredited by the Institution of Civil Engineers, UK) is critically reviewed and evaluated, aiming at enhancing core technical skills alongside those required for systems thinking solutions. Comparative evaluations considering learning outcomes and industry expectation are carried out. Based on the review and evaluation using both academic and industry insights, some insights and recommendations to improve student experience and to enhance learning environment with the emphasis on employability, systems thinking approach and industry practice are highlighted. [ABSTRACT FROM AUTHOR]

Negative outcomes such as noise and vibration generated by railways have become a challenge for both industry and academia in order to guarantee that the railway system can accomplish its purposes and at the same time provide comfort for users and people living in the neighbourhood along the railway corridor. The research interest on this field has been increasing and the advancement in noise and vibration mitigation methodologies can be observed using various engineering techniques that are constantly put into test to solve such effects. In contrast, the life cycle analysis of the mitigation measures has not been thoroughly carried out. There is also a lack of detailed evaluation in the efficiency of various mechanisms for controlling rolling noise and ground-borne vibration. This research is thus focussed on the evaluation of materials used, the total cost associated with the maintenance of such the measures and the carbon footprint left for each type of mechanism. The insight into carbon footprint together with life cycle cost will benefit decision making process for the industry in the selection of optimal and suitable mechanism since the environmental impact is a growing concern around the world. [ABSTRACT FROM AUTHOR]

Change of climate is unequivocal, and many of the observed changes are unprecedented over five decades to millennia. It is expected that the global atmosphere and ocean is increasingly getting warmer, the amount of ice on the earth is decreasing over the oceans, and the sea level has risen. According to Intergovernmental Panel on Climate Change, such temperature change is around 0.78 °C over decades. Without international collaboration towards Paris Agreement, the temperature change could potentially rise over 5.5°C in 2100. In addition, it is highly likely that even such a small change can trigger the worst of other extreme natural threats to interdependent urban and transport infrastructure systems. The vulnerability of those infrastructure systems has not been comprehensively addressed in open literature due to the fact that the actual climate change impact depends on specific differences of local environmental and geographical conditions. As a result, our research will highlight the extremes that can lead to system failure, degraded operation and ultimately, delays to train services. The emphasis is placed on the newly proposed Malaysia–Singapore high speed rail network, which can be affected by the most-frequent severe weather conditions including heavy rainfall and flash flood. It is found that tunnelling, steep cutting and ballast foundation are ones of the most vulnerable assets from a heavy rainfall or a flash flood. [ABSTRACT FROM AUTHOR]

The Paris Agreement of December 2015 signifies global unity to limit global warming to well below 2°C (above pre-industrial levels) and to pursue efforts to limit the increase to 1·5°C. The global community now agrees that anthropogenic climate change is unequivocal. According to the Intergovernmental Panel on Climate Change, the global average combined land and surface temperature has increased by 0·78°C. Although the magnitude of change in mean temperatures is relatively small, attendant extreme weather events have been shown to have increased in frequency, and are projected to increase in the future. The potential impacts of climate change on railway infrastructure and operations have not been fully assessed in the literature. The projected urban growth in Kuala Lumpur and Singapore has led to the necessity to establish a high-speed rail (HSR) system between the two. However, the existing railway network in the region has been significantly affected by severe weather conditions such as rainfall, lightning, wind and very high temperatures. This research addresses a knowledge gap regarding the potential impacts of climate change on future rail projects in the region, and points out the vulnerabilities that may lead to impaired operations and system failures. These insights are intended to inform the holistic consideration of climate change impacts in the design stage of HSR systems in Malaysia and beyond. [ABSTRACT FROM AUTHOR]

• 3D IWP minimal surface structures have been modeled and validated. • 3D printed IWP specimens have been established and experimentally tested. • Structural performance of the cellular unit has been assessed thoroughly. • Failure modes have been identified for the first time. • Discrete element modeling has been established to model the damage and failure of the structure. The Schoen I-graph-wrapped package (IWP) structures are recognized as one of the best promising cellular structures because of their high specific mechanical properties and damping ratios. The axially-loaded behaviors are critical for structural safety and durability in engineering fields. In order to extend the application of IWP structures into civil engineering, this paper investigated the axially-loaded behaviors, including compressive strength, force distribution, load-deflection pattern, energy absorption and cracking pattern, of the main and secondary Skeletal-IWP structures. Firstly, a novel method for simplifying triply periodic minimal surfaces (TPMSs) has been put forward. Then the main and secondary Skeletal-IWP units are fabricated using stereolithography technology and tested. The discrete element method (DEM) is adopted, for the first time, to simulate the axially-loaded behaviors of IWP structures with different unit cell arrangements after the validation by robust experimental results. The results reveal that the secondary Skeletal-IWP structures outperform the main Skeletal-IWP structures in compressive strength. When the unit arrangement changes from single unit to 7 × 7 × 7, the compressive strength of the main and secondary Skeletal-IWP structures increases from 9 MPa to 13.4 MPa and 9.2 MPa to 14.4 MPa, respectively. The main type shows a "X"-shaped cracking pattern, and the secondary shows a "X"-shaped cracking pattern. [Display omitted] [ABSTRACT FROM AUTHOR]

Inevitably, train and track interaction generates a travelling source of noise and vibration along the railway corridor. Railway noise is generated in various forms and spectra. The undesirable railway sound and vibration include rolling noise, impact noise, curve noise, mechanical noise, airborne noise, wheel/rail noise, structure- and ground-borne noises. The noise that is carried through the vehicle body mainly affects ride quality, customer experience and structural integrity of the rolling stocks, whereas the vibration that is transmitted from the rails to the supporting structure of the track plays a main role in rapid track degradation and potentially affects the surrounding structures. This study highlights the practical guidelines for track vibration isolation resulting from the operation of railways. Its emphases are placed on the contemporary vibration mitigation methods used in existing and ageing railway infrastructures (the so-called ‘brown field project’). Its aim was to provide the overview and lessons learnt for the future development of new vibration isolation strategies in practice. [ABSTRACT FROM PUBLISHER]

Australian railway networks suffer a large fluctuation of extreme heats each year due to their wide variety of geographical conditions. Depending on climatic, cloud and radiation conditions, an ambient temperature of 20 °C could induce an equivalent thermal load absorption of track components as much as 30 °C to 35 °C or even more. As such, relatively high turnover of timber sleepers (crossties in a plain track), bearers (skeleton ties in a turnout), and transoms (bridge cross beams) can often be observed due to their unstable deformation and rapid deterioration. This paper investigates an application for the replacement of ageing timber transoms mounted on existing railway bridges using fibre reinforced foamed urethane (FFU) transom beams, which are proven to provide environmental, safety and financial benefits. Clear benefits of the FFU material are the maintainability and constructability, especially for existing railway bridges. In this study, numerical simulations using finite element package ABAQUS have been carried out to illustrate the effect of thermal loads on the structural behaviour of a railway transom bridge. The model was developed using a case study of an actual railway bridge in Kiama, Australia and it has been validated by field data measurements. It is found that nonlinear structural behaviour of the bridge components exists at highly elevated temperatures. The better insight into the thermal load responses will lead to safer and more reliable rail stress adjustment practice, preventing rail misalignment or buckling. [ABSTRACT FROM AUTHOR]

Prestressed concrete sleepers (or railroad ties) are designed to carry and transfer the wheel loads from the rails to the track foundation. Over a period of time, a railway track could experience various types of static and dynamic loading conditions, which are attributable to commercial train operations. Previous studies have established two main limit states for the design consideration of concrete sleepers: ultimate limit states under extreme impact and fatigue limit states under repeated probabilistic impact loads. Prestressed concrete has played a significant role in maintaining the high endurance of the sleepers under low to moderate repeated impact loads. Despite the most common use of the prestressed concrete sleepers in railway tracks, their remaining lives are not deeply appreciated nor taken into account for track maintenance and renewal. The present experimental investigation was aimed at determining the residual prestressing force of railway concrete sleepers after revenue services using the dynamic relaxation technique. Fifteen sleepers were extracted from a heavy-haul rail network for testing using experimental facilities at the University of Wollongong in Australia. The structural evaluation program included quasi-static bending tests, dynamic impact tests, and tests to establish the current level of prestress in the steel wires using the dynamic relaxation technique. Two of the sleepers were evaluated for the level of prestressing forces in accordance with Australian standards. It was found that the level of prestress determined using the dynamic relaxation technique was significantly lower than that expected from the theoretical analysis of time-dependent prestressing losses for the concrete sleepers. [ABSTRACT FROM AUTHOR]

• This study stems from the critical review of more than 140 research articles available in open literatures. • It is the first to highlight the properties of recycled steel fibre with respect to cleaner applications. • Sustainability analysis of recycled steel fibre reinforced concrete is established. • The outcomes highlight best practices for sustainable and cleaner solutions using recycled steel fibres. • The insight will enable an innovative alternative to achieve net-zero infrastructures. Construction wastes have become one of critical issues in lifecycle asset management, slowing down the path towards net zero. Accordingly, the contribution of recycled materials in building design and construction is needed. In such a context, recycled steel fibres (RSF) from waste tires have been considered as an alternative to the industrial steel fibres(ISF). This paper presents a comprehensive and critical review on RSF use relatively to fibre properties, as well as the mechanical properties of RSF reinforced concrete. Both at wet and hardened state comparative analyses between ISF and RSF to improve compressive strength, splitting strength and flexural strength is performed. Moreover, based on the data of global warming potentials and prices, investigates the contribution of RSF towards sustainable development and economy in comparison with ISF. [ABSTRACT FROM AUTHOR]

Dynamic interaction between wheel and rail generates vibration and acoustic radiations transmitted through other media such as structural track systems, air, and rolling stock. Noteworthy, both wheel and rail irregularities often induce additional impact vibration and noise along the rail corridor. Rail squats and studs are typically classified as the development of any cracks that have grown longitudinally and laterally through the subsurface and become a laminated crack resulting in a depression of the rail surface. The rail defects are commonly referred to as ' squats' when they are initiated from rolling contact fatigue cracks, and as ' studs' when they are associated with a white etching layer due to wheel slips or excessive tractive effort. Interestingly, recent research shows that rail squats can be found almost everywhere, and every type of track structures, gradients and geometries in either light passenger or heavy freight traffics and for low, medium or high speed trains all over the world. A more pronounced issue appears when the crack grows and finally flakes off the rail. This paper highlights the monitoring of wheel-rail interaction over rail squat defects. Using the axle box acceleration data obtained from the calibrated track recording vehicle, the frequency spectra can be analysed. The results demonstrate an apparent influence of squats on the wheel-rail interaction over the defective sections and increased acoustic radiation at the high frequency range. The practical understanding will also enhance the development of acoustic- and vibration-based monitoring systems of rail surface defects. [ABSTRACT FROM AUTHOR]

Prestressed concrete sleepers (or railroad ties) are structural members that distribute the wheel loads from the rails to the track support system. Over a period of time, the concrete sleepers age and deteriorate in addition to experiencing various types of static and dynamic loading conditions, which are attributable to train operations. Recent studies have established two main limit states for the design consideration of concrete sleepers: ultimate limit states under extreme impact and fatigue limit states under repeated probabilistic impact loads. It was noted that the prestress level has a significant role in maintaining the high endurance of the sleepers under low to moderate repeated impact loads. This experimental investigation was aimed at static and dynamic load rating of aged railway concrete sleepers after service. Fifteen sleepers were extracted from a heavy haul rail network for testing using experimental facilities at the University of Wollongong (UoW), Australia. The structural evaluation program included quasi-static bending tests, dynamic impact tests, and tests to establish the current level of prestress in the steel wires using the dynamic relaxation technique. Two of the sleepers were evaluated for the level of prestressing forces in accordance with Australian Standards. Through diagnostic tests, the results of quasi-static bending tests produced the in-track bending capacities of sleepers that can be combined with the moments and forces anticipated over the next ten years to predict performance of the sleepers on a heavy haul coal line. The dynamic tests simulating the ability of concrete sleepers to resist extreme loading events due to heavy impact loads demonstrated that the sleepers in-track are likely to be able to resist the planned increased traffic without catastrophic failure over the next decade. Final conclusions suggest that there should be a routine test program every five years to ascertain the load rating of clustered sleepers and their fastening system in the heavy haul track system. [ABSTRACT FROM AUTHOR]

There has been a considerable increase in derailment investigations, in particular at railway turnouts (RTs), as the majority of derailments lead to lengthy disruptions to the appropriate rail operation and catastrophic consequences, being potentially severely hazardous to human safety and health, as well as rail equipment. This paper investigates the impact of climates with different features across the US on the derailments to light up a scientific way for understanding importance of climatic impact. To achieve this, official derailment reports over the last five years are examined in detail. By means of geographic segmentation associated with spatial analysis, different exposure levels of various regions have been identified and implemented into a Bayesian hierarchical model using samples by the M–H algorithm. As a result, the paper reaches interesting scientific findings of climate behaviour on turnout-related component failures resulting in derailments. The findings show extreme climate patterns impact considerably the component failures of rail turnouts. Therefore, it is indicated that turnout-related failure estimates on a large-scale region with extreme cold and hot zones could be investigated when the suggested methodology of this paper is considered. • The climate effects causing derailments at turnouts have been identified and classified. • A novel methodology dealing with the climate effects on derailments is proposed. • The relationship between turnout component failures and climate impact is assessed. • The suggested model is validated through actual derailment cases in the US. [ABSTRACT FROM AUTHOR]

• Nonlinear FE model of sleepers has been presented. • Full-scale experiments have been conducted for validation. • Crack propagations are monitored and presented. • It is the first time that crack propagations are predicted. • Prestress forces play a significant role on the crack propagation. The prestressed concrete sleeper is a primary type of sleeper for railway systems around the world. Compared with wooden and composite sleepers, concrete sleepers are of good elasticity and sufficient longitudinal and lateral resistance to ensure the stability of the track. As the railway system is developing to a heavier load and higher speed system, the cracking of concrete sleepers under dynamic load and long-term service is becoming more and more critical. It is essential to evaluate the crack behaviour of prestressed concrete sleepers. In this paper, three-dimensional FEM models have been established using Abaqus based on the brittle cracking model. After the validation by experimental results, the numerical research is performed to evaluate the crack propagation behaviours of prestressed concrete sleepers with different concrete compressive strength, different prestressing force magnitudes, and different loading rates. The results reveal that the cracking resistance of a concrete sleeper turns enhanced by improving the compressive strength of concrete and the initial prestressing force of tendons. It is also observed that the cracking becomes more progressive as the loading rate increases. [ABSTRACT FROM AUTHOR]

Excessive external vibrations could affect the normal functioning and integrity of sensitive buildings such as laboratories and heritage buildings. Usually, these buildings are exposed to multiple external vibration sources simultaneously, so the monitoring and respective evaluation of the vibration from various sources is necessary for the design of targeted vibration mitigation measures. To classify the sources of vibration accurately and efficiently, the advanced hybrid models of the convolutional neural network (CNN) and long short-term memory (LSTM) network were built in this study, and the models are driven by the extensive data of external vibration recorded in Beijing, and the parametric studies reveal that the proposed optimal model can achieve an accuracy of over 97% for the identification of external vibration sources. Finally, a real-world case study is presented, in which external vibration monitoring was carried out in a laboratory and the proposed CNN+LSTM model was used to identify the sources of vibration in the monitoring so that the impact of vibration from each source on the laboratory was analyzed statistically in detail. The results demonstrate the necessity of this study and its feasibility for engineering applications. [ABSTRACT FROM AUTHOR]

The interspersed railway track is an enhanced timber railway track, spot-replacing damaged wooden sleepers with new concrete sleepers to improve the bearing capacity of existing railway lines. Although this interspersed solution is characterised by low cost and short maintenance time, the interspersed tracks have worse stability than concrete tracks and can deteriorate quickly when exposed to extreme weather conditions such as heavy rains and floods. In many cases, heavy rains and floods are accompanied by strong winds. Ballast washaway can often be observed under flood conditions while the mass of trains is unevenly distributed on two rails due to the effect of lateral wind load and rail irregularities. The current work is the first in the world to investigate the collective multi-hazard effects of ballast washway and uneven axle loads on the vulnerability of conventional and interspersed railway tracks using nonlinear FEM software, STRAND 7. The train bogie is modelled by two sets of point loads. The maximum displacement, bending moment and twists have been studied to evaluate the worst condition. The novel insights will help the railway industry develop proper operations of interspersed railway tracks against naturally hazardous conditions. [ABSTRACT FROM AUTHOR]

The increase in demand for railway transportation results in a significant need for higher train axle load and faster speed. Weak and sensitive trackforms such as railway switches and crossings (or called 'turnout') can suffer from such an increase in either axle loads or speeds. Moreover, railway turnout supports can deteriorate from other incidences due to extreme weather such as floods which undermine cohesion between ballast leading to ballast washaway or loss of support under turnout structures. In this study, new intelligent automation based on machine learning pattern recognition has been built to detect and predict the deterioration of railway turnouts exposed to flooding conditions which is the scope of this study. Since the turnout system is very complex by nature, different features and smart filtering are explored to find the potential features for deep learning. Nonlinear finite element models validated by actual field measurements are used to mimic the dynamic behaviors of turnout supports under flooding conditions. The study exhibits that the novel recognition model can achieve more than 98% accuracy, yielding the potential capability to recognize and classify turnout support deteriorations facing extreme weather conditions which will be beneficial for responsible parties to schedule and plan maintenance activities. [ABSTRACT FROM AUTHOR]

Statistically, the actual loading conditions for railway tracks are rather dynamic and transient. The dynamic loadings due to train and track interactions redistribute from the rails to the rail pad, from the rail pad to the railway sleeper, and from the railway sleeper to the underlying ground. Commonly, railway sleeper in track systems is modeled as a beam on elastic foundation. This study makes use of a calibrated finite element model of railway sleepers in a track system, in order to investigate the resonant frequencies and associated mode shapes of railway components in interspersed track systems. The numerical model takes into account the tensionless characteristic of the elastic support as well as the more realistic partial support condition. Using a finite element package STRAND7, the dynamic finite element model of the railway concrete sleeper was precisely established. The dynamic model has then been extended to demonstrate free vibration behaviours of the railway tracks. The effect of interspersed patterns (1 in 2; 1 in 3; and 1 in 4) on railway track dynamics has been firstly investigated and presented herein. [ABSTRACT FROM AUTHOR]

• 3D FE model of interspersed tracks has been developed. • Vulnerability of interspersed tracks has been assessed. • This study is the first to assess the failure of interspersed tracks exposed to flood damage conditions. • The new insights will help track engineers to define operational restrictions in order to improve resilience capability of interspersed railway tracks. In traditional railway networks globally, timber sleepers have been widely adopted since the advent of railway systems. After a certain period of time, timbers tend to degrade and it becomes more and more difficult to seek cost-effective replacement hardwood sleepers. To provide a short-term solution, many rail infrastructure managers use an interspersing method of track maintenance. The interspersed sleeper of railway tracks, which is a spot replacement of old timber sleeper with concrete or composite counterparts, is often utilised as a temporary maintenance measure for secondary railway tracks such as low-traffic lines, yards, balloon loops or siding. Reportedly, the performance of railway lines including the interspersed tracks can quickly deteriorate when the tracks are exposed to heavy rains and floods. In many cases, ballast washaway can be often seen. This study is the world first to demonstrate the effects of ballast washaway on the vulnerability assessment of interspersed railway tracks using nonlinear finite element simulations, STRAND7. Two sets of moving point loads representing a bogie along the rails have been established to investigate the worst-case, potential actions for impaired performance of sleepers and differential settlements of the track. In this study, the emphasis is placed on the effects of ballast washaway on the maximum displacement of rails and the relative track geometries (i.e. top and twist). The maximum bending actions causing the failures of the track components are also investigated. The new insights will help track engineers develop appropriate climate change adaptation methods and policies for operations of interspersed railway tracks facing extreme rainfall and flooding conditions. [ABSTRACT FROM AUTHOR]

Recently updated information has raised a concern over not only the existing cost-ineffective design method but also the unrealistic analysis mode of railroad prestressed concrete sleepers. Because of the deficient knowledge in the past, railway civil engineers have been mostly aware of the over-conservative design methods for structural components in any railway track, which rely on allowable stresses and material strength reductions. Based on a number of proven experiments and field data, it is believed that the concrete sleepers which complied with the allowable stress concept possess unduly untapped fracture toughness. A collaborative research project run by the Australian Cooperative Research Centre for Railway Engineering and Technologies (RailCRC) was initiated to ascertain the reserved capacity of Australian railway prestressed concrete sleepers designed using the existing design code. The findings have led to the development of a new limit states design concept. This briefing highlights the conventional and the new limit states design philosophies and their implication to both the railway and the public community. [ABSTRACT FROM AUTHOR]

Abstract: On railway track structures, dynamic impact loads with very high magnitude but short duration are often caused by wheel or rail abnormalities such as flat wheels and dipped rails. The possibility of the large impact loading to cause an extreme failure to an in situ concrete sleeper could be very low about once or twice in the design life cycle. However, to the current knowledge, the behaviour of the in situ prestressed concrete sleepers under the ultimate impact loading has not yet been comprehended, resulting in the design deficiency. A high-capacity drop-weight impact testing machine was thus constructed at the University of Wollongong, in order to evaluate impulsive resistance of in situ prestressed concrete sleepers under impact loads. This paper describes the detail of the high-capacity impact testing machine, as well as the instrumentation, the calibration, and the analysis of failure mode, crack propagation, flexural toughness, and energy absorption mechanisms with respect to railway prestressed concrete sleepers. The impact tests were carried out using the prestressed concrete sleepers manufactured in Australia. An in situ track test bed was simulated in laboratory and calibrated against the frequency response functions obtained from the experimental modal analysis. The experiments using the high-capacity impact testing machine to investigate the impact energy transfer mechanism of the prestressed concrete sleepers are highlighted. [Copyright &y& Elsevier]