The ‘Dynarat’ computer simulation of ratcheting wear and failure of rail steel has been developed at Newcastle University over the past decade based on laboratory tests and analysis of British normal grade (R220) rail steel. The aim of this thesis is to develop material models for Dynarat that can be used to predict wear and rail life for R260 rail steel, which is used widely in Europe and increasingly in Britain, and also for newer premium grade pearlitic rail steels. Laboratory twin-disc testing and metallurgical material analysis were used to obtain data for characterising and modelling material response to repeated loading. The relationship between material hardness and plastic shear strain is central to the material model used in the Dynarat simulation, and is determined for the materials tested here by studying the measured hardness and plastic strain. Additional calibration of the wear rate was achieved by performing Dynarat simulations that closely matched the laboratory tests. In addition to the material model development, the contact stress model used by Dynarat for modelling wheel-rail contact is improved. Previously the driving stress for plastic strain accumulation was the orthogonal shear stress in the plane of the simulation. In the new model, plastic strain accumulation is now made directional, with components in the x and y directions. Partial slip is now implemented in the 3D simulation, to approximate the real wheel-rail contact, with both contact region and adhesive zone modelled as ellipses. Two types of high-speed train at two curves on the UK’s East Coast Main Line have been simulated with the new computer model to study the effects of traffic mixtures. Wear rates and time until crack initiation are obtained. The new model provides a tool to help rail/wheel manufacturers to choose the best steel, and for maintenance personnel to predict rail wear and cracks, and thus to help plan grinding schedules in order to optimise rail life and safety.

Maintaining track on the UK railway network accounts for a large proportion of the total operating costs. During the year 2012/ 2013 Network Rail spent £391million on the maintenance of track. In order to maintain and operate the railway to a high standard at a lower cost, an asset management strategy is needed. This study uses a model to predict the effects of different asset management strategies. An optimisation routine is then used to obtain a number of optimum strategies based on maintenance cost and track quality. The first part of this study utilises data on the UK rail network track geometry, including records of maintenance performed, to analyse the effects of corrective maintenance on track geometry degradation . The Weibull distribution is used to analyse the distributions of times for the track geometry to degrade to specified states following maintenance. The quality of the track geometry is investigated after corrective maintenance has been performed. This study has shown that such maintenance becomes less effective the more times it is carried out and there is a point at which a renewal becomes the most cost effective solution. The second part focuses on a Petri net modelling approach to rail track asset management. Two Petri nets have been developed- a single track section model and a multi track section model. These are used to predict the track condition over time accounting for a specified asset management strategy. The results of the analysis show that Petri net models are an accurate technique for modelling maintenance strategies. In the final part of this study a multi objective genetic algorithm was used to maximise track quality while minimising the life cycle cost. This has been accomplished by determining the optimum geometry measurement interval, number of maintenance machines on the network and maintenance and renewal criteria. Such a predictive approach would be used by rail operators to support the setting of the maintenance strategy.

It is generally observed that the condition of rail tracks degrades rapidly over time until and unless effective maintenance is carried out. In the rail industry, rail maintenance actions are usually reactive, which means that maintenance is carried out after a defect has been identified. Unfortunately, this approach can lead to general safety concerns and may result in costly maintenance. Predictive maintenance, which aims to predict the future behaviour of track degradation based on the analysis of already recorded data, can be used to identify defects in advance, thus providing a solution for the above safety and cost concerns. Two important questions for which answers are sought in predictive maintenance of rail track are: where does the fault occur and when. The aim of the research presented in this thesis is to develop a novel predictive rail track degradation model that answers the above questions. The proposed model consists of an alignment component for effective alignment of data and a degradation component for understanding rail track degradation based on rail profile and track geometry parametric analysis. The thesis takes an incremental approach to data alignment proposing three different algorithms namely, distance alignment, fixed window based alignment and parameter based alignment. It is proven that the latter approach provides the most accurate data alignment algorithm. The degradation component of the proposed model is based on a comprehensive multivariate and univariate analysis. In multivariate analysis, parameters of a base file i.e. a file consisting of parameters belonging to the same segment of the rail track at a given time of measurement are predicted using all other parameters of the same file. In univariate analysis, every parameter of a given base file is predicted, temporally, from the corresponding parameters in the previous base files. Such contribution analysis manifests the level to which each parameter contributes in predicting other parameters and over time. Subsequent to univariate and iii multivariate analysis the predictive errors are thresholded into either exceedences i.e. they exceed the threshold line, needing immediate maintenance, or normal i.e. they are below the threshold line, needing no immediate maintenance. The research presented in this thesis shows that in multivariate analysis, rail profile parameters were predicted with 97% prediction accuracy below threshold, whereas track geometry parameters were predicted with 99% prediction accuracy below threshold. Both univariate and multivariate analysis will serve as the basis in monitoring track conditions and thus finding track degradation problems. This will greatly aid in planning predictive track degradation by providing an objective means of evaluating track conditions and hence the over all life of the rail track will increase.

The use of GNSS in the railways for passenger information services and selective door opening is already commonplace but the advancement of this increasingly popular navigation technique into safety of life rail applications has been hindered by the unknown level of measurement error caused by the local rail environment, especially that due to multipath. Current state of the art receiver technologies are discussed along with the additional advantages of signal differencing using local base stations. Limiting factors for hardware in a kinematic environment are also discussed and specific examples to the rail environment highlighted. Safety critical analysis techniques such as FMEA, HAZOP and FTA are reviewed to illustrate the evaluation of safety integrity values and the possibility of system risk, leading to the formation of a structured safety case. Three main data sets from electrified, rural and urban rail environments have been collected using dual frequency geodetic receivers in order to enable analysis of multipath effects in normal railway operations. The code and phase data have been combined to compute fluctuations in multipath errors and these have been used to characterise this effect in both space and time. Where phase positioning is possible comparisons with standard code-based positions have been made to assess the overall quality of the type of GNSS positioning expected to be operationally-viable on the railways. Experiments have also been undertaken to evaluate the possible effects of electromagnetic radiation from overhead cables used to power the trains. Finally, the ways in which the results of these experiments can be used to help build a safety case for the use of GNSS on the railways are discussed. Overall it is concluded that it is unlikely that multipath errors or electromagnetic interference will be the limiting factors in utilising GNSS for safety-critical railway applications.

The basis of all railway signalling activities is the knowledge of the position and velocity of all trains in the system. The railways traditionally rely on train detection systems for this knowledge. However, the dependence of these systems on railway infrastructures limits their ability to cope with the advent of new high-speed lines and the development of freight networks across the Europe. Hence, there is a need for the introduction of modern positioning technologies into the railways. Unfortunately railways provide an unfriendly environment for satellite-based radio positioning systems (GNSS). For this reason it is common to integrate GNSS with low-cost inertial sensors (INS) but such systems cannot meet all railway positioning requirements. This thesis examines the potential of enhancing such an integrated GNSS/INS system with a digital route model (DRM). The study is carried out through a series of simulations of typical railway positioning scenes. A simulated database of GNSS, inertial and DRM data is built from real GPS data collected on a rail line between Norwich and Lowestoft. Several tests are first performed to test the validity of the database. Simulations are then done with a number of traditional INS/GPS integration architectures to test the possible performance of each system in the railway environment using lowcost INS sensors. The DRM-aiding is then realised through an integration with the GNNS/INS system via an extended Kalman Filter. Results from the study confirm the need for additional positioning information for an integrated system with low-cost inertial sensors to deal with difficult satellite signal situations such as tunnels, deep cuttings and covered stations. It is shown that a DRM leads to significant improvements in the overall system positioning performance. Also the optimal configuration, in terms of point spacing and accuracy, for a digital route model is selected from amongst simulated candidates.

The high frequency dynamic behaviour of railway track, in both vertical and lateral directions, strongly affects the generation of rolling noise as well as other phenomena such as rail corrugation. One aspect that has received little attention is the coupling between the vertical and lateral directions. This thesis sets out to build an analytical model of a railway track with three principal targets: to improve the modelling for lateral vibration compared with existing models, to identify the most important sources of coupling between the vertical and lateral directions and to quantify the implications for rolling noise phenomena. Simple models for the axial, torsional, vertical and lateral vibrations of beams are first introduced. The results from these models are analysed based on their dispersion curves and their characteristic behaviour is identified. Furthermore, effects of cross-section asymmetry, shear deformation, rotational inertia, restrained warping and curvature are considered, as well as the fact that the loads at the rail head do not always act through the centroid of the rail section. These beam models are then brought together to formulate a fully coupled beam model. An elastic foundation is then introduced to the beam model to represent the railpads and the dispersion characteristics of the whole track are discussed. Subsequently, the effect of the foundation location is investigated, as well as the inclusion of additional layers of masses and springs, representing the sleepers and ballast. Two different sleeper models are introduced. The first is that of a simple mass allowed to translate and rotate, representing a single block of a bibloc sleeper. The second is that of a flexible finite length beam accounting for vertical, lateral, axial and torsional vibration, representing a monobloc sleeper, which is more widely used in railway tracks. The response of the beam model is compared against measurements performed on sleepers in the laboratory. An average error of less that 1% is observed for the natural frequency of all modes, excluding the first mode. This mode is most influenced by the sleeper cross-section variation which is not directly accounted for in the model.

While railway relies on the knowledge of train position to manage operations, systems currently used to locate trains have a limited accuracy, which limits the network capacity. A positioning system combining Global Navigation Satellite Systems (GNSS) with additional sensors has the capability to provide high accuracy positioning information to support railway operations. However, to reach such accuracy, the different sources of error affecting GNSS measurements need to be mitigated. Among these error sources, multipath signals are a prime concern as they are particularly challenging to mitigate due to their high variability along the train path. The aim of this thesis is to mitigate the effect of multipath on GNSS code based single point positioning in the railway environment. To achieve this aim, the code multipath error in the railway environment is characterised. Measurement weighting techniques traditionally used to mitigate the effect of multipath on the positioning solution are investigated and a novel weighting method based on the train heading and the satellite position is developed and tested. The results show variable levels of performance, with no single method outperforming the rest along the entire track dataset analysed. In summary, the elevation and the new heading based methods are shown to complement each other, with the latter performing better (34% of the time) where there are trackside obstacles.

The ever growing demand for public transportation and the need to integrate effective transport systems into urban life have led to an increase in the planning and construction of new railway systems in many countries around the world. These projects boast immense economic benefits, including high passenger capacity and reduction in commuting times. However, they are strongly opposed from an environmental point of view, not least the noise and vibration that are generated from their operations and subsequently transmitted into nearby buildings. In order to reduce the level of impact of the rail vehicles on the tracks, and subsequently the environment, railway tracks are commonly constructed with resilient elements, e.g. railpads. The dynamic properties of these elements have significant effects on noise generation, track and ground-borne vibration. It is important to develop understanding of the dynamic behaviour of railway tracks, through numerical modelling and/or experimental testing, in order to devise effective vibration countermeasures. To this end, many numerical models have been developed, most of which assumed linear and homogeneous track properties. However, many studies have shown that resilient elements exhibit pronounced nonlinear behaviour and that variability in track properties exists along the length of the track. In this study, novel approaches for incorporating nonhomogeneous and non-linear railpad properties in the modelling of railway track dynamics have been developed. A new method, called the Double Fourier Summation, have been used to account for nonhomogeneity in track foundation properties. To account for nonlinearity, on the other hand, constitutive relationships have been derived for the static and dynamic rail pad properties based on experimental data. These are then included into a time domain finite elements track model in order to study the effects of nonlinearity on track dynamics. The key findings of this research emphasise the necessity of including non-homogeneous and nonlinear behaviour of track resilience into the modelling of track dynamics. Large disparities in the track displacement, reaction-forces and wheel/rail interaction forces (more than 20 dB in some cases), have been observed between simplified linear homogeneous models and the more complex nonhomogeneous and nonlinear models presented in this work.

This thesis describes the development and validation of a versatile and Flexible Track System Model (FTSM) and its integration into a commercial railway vehicle dynamics software tool. The work was initiated to fill a gap in current disciplines and tools used to investigate problems relating to vehicle and railway track dynamics due to a lack of correlation between Finite Element (FE) and MuItibody System (MBS) based models. The. FTSM track model was validated against results from laboratory testing and compared with existing models. It was then used to study several aspects of the deterioration of ballasted track under the dynamic loading of passing vehicles at speeds, including consideration of the non-linear nature of the track support condition such as sleeper voiding and variable sleeper support stiffness. . The research contributes to the fundamental understanding of the vehicl~-track interaction forces and particularly to the relation that exists between wheel-rail contact forces and track forces. It shows that.in order to accurately predict track degradation forces, a detailed flexible track model is essential. The major differences in terms of wheel-rail contact condition and forces obtained from the conventional simplified track models and from the FTSM are also highlighted. The presence of higher frequency modes of vibration of the flexible track proves essential for those studies involving local and sudden track events. The model was also applied to the analysis and design development of innovative track structures that seem to offer several advantages with respect to conventional ballasted tracks, most importantly a more consistent or continuous support to the rail. This characteristic is shown to be essential for minimising the interactive cycle of dynamic interaction forces and track deformation leading to track settlement and deterioration.

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