The exchange of information is crucial to the operation of railways; starting with the distribution of timetables, information must constantly be exchanged in any railway network. The slow evolution of the information environment within the rail industry has resulted in the existence of a diverse range of systems, only able to exchange information essential to railway operations. Were the cost of data integration reduced, then further cost reductions and improvements to customer service would follow as barriers to the adoption of other technologies are removed. The need for data integration has already been studied extensively and has been included in the UK industry's rail technical strategy however, despite it's identification as a key technique for improving integration, uptake of ontology remains limited. This thesis considers techniques to reduce barriers to the take up of ontology in the UK rail industry, and presents a case study in which these techniques are applied. Amongst the key barriers to uptake identified are a lack of software engineers with ontology experience, and the diverse information environment within the rail domain. Techniques to overcomes these barriers using software based tools are considered, and example tools produced which aid the overcoming of these barriers. The case study presented is of a degraded mode signalling system, drawing data from a range of diverse sources, integrated using an ontology. Tools created to improve data integration are employed in this commercial project, successfully combing signalling data with (simulated) train positioning data.

The word 'strategy' has represented many concepts since it originated in a military domain. Fundamentally, it is concerned with determining how best to direct systems in a changing world. However, in today's increasingly complex and vertically separated sectors, conventional top-down approaches to strategy design are becoming less applicable. The proverb 'I am because you are' encapsulates the idea that the world is not formed of independent, separate entities, but that all beings and actions are connected. This thesis puts forward a case for applying that way of thinking in a systems approach to strategy design. The proposed approach comprises three processes which are aligned with systems engineering principles, to plan, capture and communicate strategy. It is argued that strategy documents produced by following the approach would be clearer and more rigorous. To the field of strategy, this research offers a language framework for discussing strategy concepts, a new approach for designing strategy, and pragmatic guidance for strategy design exercises. In the field of systems thinking, it contributes to the challenge of translating systems engineering principles for non-traditional domains.

Air pollution from DEEEs is becoming an increased international concern, and whilst attention has been primarily focused on the automotive industry, concerns have also been raised about emissions from diesel rail vehicles. The research is designed to assess the hypothesis that diesel rolling stock severely impacts air quality at Birmingham New Street station due to the station’s enclosed nature. To assess this hypothesis, an extensive series of long term measurements were made at Birmingham New Street station. The monitoring campaign consisted of diffusion tube measurements, to measure NO2 at locations in and around the station, followed by measurements of NOx, PM, CO2 and BC at stationary and mobile sites at the platform level. The results illustrated that diesel trains serving the station elevated pollutant concentrations, particularly oxides of nitrogen. During the sampling campaign the average NO2 concentration in the centre of platform 10/11 was 407 μg/m3, approximately 10 times greater than the EU ambient air quality limit. NO exceed its WEL 35% of the time during the monitoring campaign for the same site. Furthermore, this research concludes that CO2 is not suitable as a surrogate for assessing DEEEs exposure. NO2 concentrations exceeded their relevant exposure limits, whilst CO2 did not exceed the ventilation system’s 50% speed threshold, as a result it is unlikely that harmful pollutants were being successfully exhausted from the station. The environmental analysis identified a potential trapped vortex in the West end of the station, which could have an impact on the ventilation system in place at Birmingham New Street station. It is clear that this research has been pivotal in driving a focus towards air quality with the railway industry and has prompted further research at other enclosed railway stations.

The issue of managing a large and complex railway system with continuous traffic flows and mixed train services in a safe and punctual manner is very important, especially after disruptive events. In the first part of this thesis an analysis method is introduced which allows the visualisation and measurement of the propagation of delays in the railway network. The BRaVE simulator and the University of Birmingham Single Train Simulator (STS) are also introduced and a train running estimation using STS is described. A practical single junction rescheduling problem is then defined and it investigates how different levels of delays and numbers of constraints may affect the performance of algorithms for network-wide rescheduling in terms of quality of solution and computation time. In order to deal with operational dynamics, a methodology using performance-based supervisory control is proposed to provide rescheduling decisions over a wider area through the application of different rescheduling strategies in appropriate sequences. Finally, an architecture for a real-time train rescheduling framework, based on the distributed artificial intelligence system, is designed in order to handle railway traffic in a large-scale network intelligently. A case study based on part of the East Coast Main Line is followed up to demonstrate the effectiveness of adopting supervisory control to provide the rescheduling options in the dynamic situation.

The development of the alternating current field measurement (ACFM) technique for high-speed inspection of railway wheels/track is important to ensure the integrity of railway assets. The stress and conditions at the wheel/rail contact patch, severity of rolling contact fatigue (RCF) damage and changes in microstructure and hardness with tread depth for railway wheels are investigated. This study employs experimental measurement of RCF defects in railway wheels to understand ACFM sensor signal - RCF defect relationships. The influence of sensor frequency and speed, sensor angle relative to crack angle, lift-off distance, crack propagation angle and inter-crack spacing distance are investigated. Low rather than high frequency sensors are better suited at sizing cracks in railway wheels and track. The optimum signal is obtained when the sensor is oriented parallel to the crack angle. The signal is reduced at higher speeds. The maximum change in the normalised Bx signal component of the sensor’s magnetic field is greater for closely spaced cracks (< 5 mm) and thus overestimates the defect. Inter-crack spacing distances of 15-20 mm yield estimates for crack pocket depths that are oversized by 20-36%. The inner cracks in a cluster with four defects yields higher Bₓ values than expected and thus significantly over sizes the defects at 15-20 mm inter-crack spacing distances, whereas, the sensor provides reasonable depth estimates for the outer cracks. Crack propagation angle affects the signal. Scans conducted with the probe oriented at 90° to the cluster of cracks consisting of a deep central crack surrounded by shallow cracks results in a distinct central sensor Bₓ signal that consists of a peak due to a flux leakage effect, thus, identifying the critical defect.

The author of this thesis deals with the issues of real time traffic management in junction areas and bottleneck sections on mainline railways in the event of service disturbances. A systematic methodology is proposed for modelling and solving real time train rescheduling problems in junction areas and bottleneck sections, including train re-sequencing and train re-timing. A formal mathematical model, the Junction Rescheduling Model (JRM) is proposed, based on a Mixed Integer Programming (MIP) to minimise a Weighted Average Delay (WAD). An innovative algorithm based on Differential Evolution algorithm, named DE_JRM is proposed for solving real time train rescheduling problems formulated with JRM. The performance of the algorithm DE_JRM has been evaluated with a stochastic method based on Monte-Carlo simulation methodology. The evaluation results show a good performance for both flyover and flat junctions compared with First Come First Served (FCFS) and a conventional ARS strategy. The author also extends the proposed methodology, including JRM and the algorithm DE_JRM, to model and solve real time train rescheduling problems for bottleneck sections of railway networks. Finally, an integrated system architecture for the traffic management and train control is introduced for system implementation of the proposed methodology of train rescheduling in junction areas and bottleneck sections on mainline railways.

The rail industry has focused on the improvement of maintenance through the effective use of online condition monitoring of rolling stock and rail infrastructure in order to reduce the occurrence of unexpected catastrophic failures and disruption that arises from them to an absolute minimum. The basic components comprising a railway wheelset are the wheels, axle and axle bearings. Detection of wheelset faults in a timely manner increases efficiency as it helps minimise maintenance costs and increase availability. The main aim of this project has been the development of a novel integrated online acoustic emission (AE) and vibration testing technique for the detection of wheel and axle bearing defects as early as possible and well before they result in catastrophic failure and subsequently derailment. The approach employed within this research study has been based on the combined use of accelerometers and high-frequency acoustic emission sensors mounted on the rail or axle box using magnetic hold-downs. Within the framework of this project several experiments have been carried out under laboratory conditions, as well as in the field at the Long Marston Test Track and in Cropredy on the Chiltern Railway line to London.

Through the use of new communication-based train control (CBTC) systems, modern metro railways have been able to provide a more efficient, more reliable and more eco-friendly transport services. The main advantages of the CBTC systems are achieved by utilising modern communication technologies. The performance of the communications network is dependent on a well-designed access point (AP) deployment, as this determines the overall communication capability and impacts the cost. In this thesis, a systematic methodology is proposed for formulating and solving AP deployment planning (ADP) problems in two scenarios: (i) a tunnel section area; and (ii) a real-world metro system. Different mathematical models are presented for modelling the ADP problem in these two scenarios. In addition to mathematical models, an exhaustive search and a customized search algorithm, which uses a multi-objective evolutionary algorithm based on decomposition (MOEA/D), are proposed for solving the ADP optimisation problems. The methodologies are applied to the scenarios mentioned above. To evaluate the optimisation results, the optimised AP deployments are tested on a simulation platform integrating a railway network simulator and a communication network simulator. The test result shows that with the optimised AP deployments the DCS can achieve a better performance while using fewer APs.

Energy consumption in electric locomotives is principally the power consumed in traction motors. In order to reduce this energy consumption, the motion resistances of the train need to be reduced. These resistances include aerodynamics; inertial and grade forces; curving resistance; and bearing and wheel/rail friction. Though many factors such as gradient resistance cannot be modified, if a control system is included, curving resistance can be minimised by reducing the energy losses in the contact patches between wheel and rail. Therefore, operational practices could be modified in order to obtain the most appropriate wheelset attack angle between wheel and rail, and appropriate train speed. One solution is to implement a steering control system. The function of this control system is to monitor and control the wheelset lateral displacement or the attack angle of the wheelset. This could reduce the energy dissipated at the contact points between wheel and rail, consequently reducing the energy consumed by traction motors in railway vehicles. Therefore, the work presented in this thesis aims to design and develop a control method for combined vehicle traction and wheelset active steering control systems and to assess the energy efficiency of a rail vehicle under typical operational conditions. In order to achieve these aims, two dynamic models of a typical railway vehicle have been developed in MATLAB and Simulink. The first model comprises the electrical traction and mechanical system passive system). The second model includes the passive and the wheelset active steering control system (active system). These models are used to determine the relationship between traction energy consumption and the energy dissipated in the contact points between wheel and rail, and to compare the passive steering system to the wheelset active steering control system, determining the possibilities for energy saving. In order to assess the influence of the wheelset active steering control on the relationship between wheel and rail contact forces and traction power a series of deterministic track features are set comprising curve radii with different cant deficiencies and wheel conicities. Also a typical track profile from Leeds to Hull is used. From these simulations, the traction energy consumption, energy dissipated at the contact patches, and energy consumed by the steering actuators are calculated. Statistical analyses are used to understand the relationship between the traction power and wheelset motion dynamics (lateral displacement and attack angle). The active vehicle model scheme is used to investigate the improvement of the energy efficiency of a railway vehicle using active steering. The wheelset active steering control system analysis shows whether different combinations of vehicle speed, wheelset conicity and track curve radius lead to a reduction, no reduction, or an increase intraction power consumption. The probability of high power consumption under different conditions is assessed to ensure that it is reduced wherever possible. The ability of a forecasting model to predict the traction power consumption behaviour of railway vehicles from the wheelset motion dynamic is assessed. Findings show that the overall prediction accuracy is fairly similar to the power measured from the passive vehicle running on a track from Leeds to Hull. However, the algorithm does not perform effectively for the deterministic track features. Finally, the benefits of implementing wheelset active steering control systems in terms of the mitigation of contact forces between wheels and rails and how this mitigation influences traction energy consumption are evaluated to determine under what conditions energy can be saved.

The argument for this thesis is that patterns of past engineering and operational development can be used to support the creation of a strategy for future development and that, in order to achieve this, a corporate understanding of the history of the engineering, operational and organisational changes in the business is essential for any railway undertaking. The research shows that a railway is a complex system, where the operational life of much of the hardware is greater than the time employees spend in service, so it is common for the origins and reasons for systems on the railway to be forgotten. This knowledge can be lost when staff retire or leave. For new staff, little attention is paid to history and development during induction; indeed, such knowledge may not even be considered necessary or relevant. London Underground is used as a case study to show how the history of the system has impacted on the design of rolling stock. The work concludes that it is essential for railway employees to understand the way in which systems and operations have evolved on a railway during its history. The author proposes new processes that include historical corporate knowledge in future business development.