A new failure criterion for discriminating good and bad (overheated) railroad car wheels is proposed. This criterion can replace the conventional “four inch" discoloration rule. The procedure for the new discrimination criterion is based on the fluctuations of the azimuthal residual stress in the tread of the wheel. This criterion is based on a maximum likelihood statistical analysis of data obtained from six different wheels as deterrmined by x-ray diffraction. Of these locations, the analysis showed the tread, and perhaps a critical point on the top of the flange, to be the most sensitive to residual stress. The variance analysis showed that fluctuations in stress at the most sensitive location in the tread appeared to be related to the service history. The residual stresses showed an oscillatory pattern in the hoop direction around the wheels. Extension of the measurement technology to the use of magnetoelastic stress measurement is proposed. To evaluate the inaccuracy in stress data possible from a large sample with curved surface, corrections for a deliberate tilt of the plane of the x-ray diffractometer from the normal to the sample surface have been developed. Analysis of different misalignments are discussed. To validate our x-ray residual stress data, residual stresses were also measured by hole drilling. Excellent agreement between two techniques was found. Finally, stress variation with depth below surface was determined by the hole drilling technique. / Ph. D.

The use of on-call work in industry has now surpassed that of shiftwork and night work. Industries as a whole make use of on-call work daily as a way to maintain 24/7 operations whilst also reducing costs. Despite this, on-call work remains underresearched and no best practice or management guidelines are available. As the first substantial piece of human factors work examining on-call work in the rail industry, this thesis has the overall aim of increasing the understanding of on-call scheduling systems of work, and also to provide recommendations to the planning and management of on-call work in the rail industry which may also be applied in other industries. A semi-structured interview study with 72 rail maintenance on-call workers of Great Britain rail infrastructure owner and operator (Network Rail) explored on-call arrangements in place and the perceived unwanted consequences of this type of work. Anxiety, fatigue, and reduced well-being were perceived as the main consequences of working on-call. The findings also indicate that when discussing on-call there are three separate on-call situations; being on-call, receiving calls, and responding to calls; which influence the study variables differently. From the key themes identified initially an on-call questionnaire for managerial staff was developed and data from across the country generating 479 individual responses. A two-week diary study (one week on-call and the week after) with 26 participants aimed to collect real-time ratings. Results indicated that working on-call was perceived as a leading cause of stress, poor quality of sleep and fatigue. This is due to the inherent unpredictability of on-call work, which is the key differentiating factor between on-call work and other types of working-hours systems. Receiving and responding to calls were perceived as detrimental to general well-being both to workers and their families, fatigue, and performance. The work performed for this thesis allowed the development of the first on-call specific framework that identifies not only the key factors at play but also the relationships between them. It presents a set of principles or theories that other researchers can use to guide future research and that industry professionals can use to deliver more human friendly on-call work management processes and procedures.

This thesis presents work undertaken in conjunction with Network Rail in the area of planning and re-planning in railway environments. It aimed to study a real world signalling environment to understand the strategies signallers use when re-planning and how decision tools can be designed and integrated into existing signalling environments to support proactive planning. The main research focused on two case studies: A graphical tool developed by signallers to assist in managing station areas; and the rollout and uptake of a graphical time based planning tool. The first case study consisted of interviews and observations investigating how signallers currently plan (in and around station areas) and what existing tools and artefacts are used, followed by an experiment to compare different tools. It was found that signallers who were using a graphical based tool to assist in managing station areas were able manage disruption more efficiently than signallers using a list based tool. The second case study investigated an existing electronic tool called the Train Graph that had already been implemented. Interviews, observations and questionnaires were used to gather data on the opinions and general uptake of the Train Graph. Trust and prior experience were found to be the significant driver of end user behaviour and uptake of the technology. One key output of this research was a tangible framework that can be used by Network Rail to guide design and implementation of future decision support tools and artefacts. The framework considers the artefact design and various inputs including task characteristics and organisational context as an indicator of performance. If used at an early stage of product development the framework and associated guidelines can be used to influence system design and establish how key implementation considerations impact upon user uptake and trust of the design.

The railway industry is today broadly recognised as a complex sociotechnical system that operates under considerable pressures for increased capacity and reliability. These pressures impact across the industry, in particular on rail engineering because of its responsibility in providing and maintaining the rail infrastructure. Within rail engineering, there is a growing need to address safety and operational risks emerging from high complexity. Planning has been identified as a fundamental organisational function for the safety and efficiency of engineering work. Within this scope, this thesis recognises in the planning of rail engineering work the characteristics of complex sociotechnical systems and investigates planning activities as a part of a wider rail engineering system. Resilience engineering has been recently proposed as a safety management approach that focuses on the development of means for better coping with the variability and uncertainty inherent to large scale complex sociotechnical system. The research documented in this thesis proposes the use of a resilience engineering based approach as a way to improve the ability of the rail engineering planning system to successfully contribute to the safety and efficiency of engineering work. Overall, the purpose of this research was to describe and understand human and organisational factors of rail engineering planning, understand planning performance in view of the support it provides to work delivery, and investigate improvement to the planning system based on resilience engineering concepts. A contribution to the development of resilience engineering as a discipline was also made, mainly through the investigation of possible methods for measuring and monitoring system resilience. The thesis has taken a research approach with emphasis on extensive top-down and cross-organisational exploratory work of the engineering work planning process. This was achieved through the use of quantitative and qualitative methods, namely the analysis of archival data on operational and safety performance, interviews, observations, and a questionnaire. The integration of the researcher within Network Rail’s Ergonomics National Specialist Team (NST) was fundamental for the access to a wide range of data and for the employment of a participant observation approach. The engineering work planning system is described as a complex decision making process, ranging from high level strategic business decisions down to the definition and scheduling of work delivery details. The main human and organisational factors that either hindered or facilitated planning decision making were identified and archival data were used to study planning performance. Results from these research steps were then used to support the understanding and measurement of resilience in planning. Data were interpreted in view of the resilience literature and used as basis for the investigation of potential measurement tools and system interactions with relevance for the understanding of resilience as an emergent system property. The methods used permitted a detailed description of the planning process and the identification of planning performance features within the wider frame of the rail engineering system. Human, organisational and system level factors were identified, which contributed to the understanding of planning and the identification of constraints and facilitating factors on decision making processes. Throughout the duration of this project, contributions to the development of resilience engineering and its methods were made, whilst identifying sources of resilience in the planning system and contributing to the development of measurement tools by means of a questionnaire approach. The understanding of resilience in rail engineering planning was used as a support for recommendations towards the improvement of the planning function’s ability to cope with operational pressures and successfully support work delivery.

The philosophy of research at the University of Texas – Robotics Research Group (RRG) is towards creating a foundation for an open architecture, reconfigurable intelligent machines to meet wide breadth of operational needs. An intelligent system is the one which has complete knowledge of its operating characteristics at all times (updated in real-time) and it can make on-the-fly decisions to adapt itself to the different conditions or present the best possible options to the human decision maker under specified and ranked criteria. The reality of all complex system is that they are inherently non-linear with coupled parameters. The traditional approach dealing with such systems assumes linearized models, imposing conservative bounds on the operational domain and thus limiting performance capability of the system. Recent advancements in sensor technology and availability of computational resources (embedded processing) at low cost have made real-time intelligent control feasible for complex systems. The computational intelligence envisioned in modern intelligent machines will enhance the system performance and will provide capabilities such as criteria based control, identification of incipient faults, condition based maintenance, fault tolerance, and ability to monitor performance parameters in real-time. The first step in this process is to equip a system with a comprehensive suite of sensors. These sensors will provide real-time data and awareness about both, the internal system states and the external/environmental operating conditions. The aim of this work is to establish an argument in favor of using multiple sensors in all complex electro-mechanical systems. The report discusses numerous benefits of a multi-sensor environment with suitable examples and attempts to justify its pressing need in all the existing complex mechanical systems. Case studies for a multi-sensor environment in railroad freight cars and vehicle systems are presented. Sensing requirements in freight train and vehicle systems are evaluated and suitable sensor technology and commercial sensor options are suggested for decision makers. In addition to benefits, challenges in a multi-sensor environment such as sensor noise, cabling complexities, signal processing, communication, data validation and data management, sensor fusion, information integration, maintenance etc. are addressed and best practices to alleviate these complexities are discussed in the report. This effort lays out a foundation for developing a multi-sensor system and will enable computational intelligence and structured decision making in the system. / text

This thesis examines the effect of automation in the rail signalling environment. The level of automation in a system can be described as ranging along a continuum from manual control to fully autonomous automation and development of appropriate automation for a system is likely to enhance overall system performance. Network Rail, the company which owns, operates, and maintains the rail infrastructure in the UK, envisions increasing levels of automation in future rail systems, but prior to this research, little structured evaluation of current automation had been undertaken. The research performed for this thesis set out to examine the impact of automation on rail signalling. A rail automation model was developed to illustrate the levels of automation present in different generations of signalling system. The research focussed on one system in particular, the Automatic Routing System (ARS). The ARS has been present in modern signalling centres since the late 1980s. It uses timetable information to set routes for trains arriving on its area of control and incorporates complex algorithms to resolve conflicts between trains. Multiple methods were used to investigate current signalling automation. An understanding of the signalling domain underpinned the research, and a model was developed to illustrate the type and level of automation present in different generations of current signalling systems. Structured observations were employed to investigate differences in activity between individual signallers. As a part of this study, a relationship was found between observed intervention levels and some of the trust dimensions identified from the literature. A video archive analysis gave initial insight into some of the issues signallers had with automation, and semi-structured interviews carried out with signallers at their workstations built on these themes. The interviews investigated four areas; signallers’ opinions of ARS, system performance issues, knowledge of ARS, and interaction with ARS. Data were gathered on a wide variety of individual issues, for example on different monitoring strategies employed, interaction preferences, signallers’ understanding of the system and their ability to predict it. Data on specific issues with ARS also emerged from the interviews, for example the impact of poor programming and planning data, and the poor competence of the system, particularly during disruption. An experiment was performed to investigate the differences between different levels of automation under both normal and disrupted running. The experiment gathered quantitative data on the effect of different levels of automation on workload and performance in addition to eye tracking data which were used to gain insight into signaller monitoring strategies. The results indicate that ARS does reduce workload and increase performance, and it does so in spite of deficiencies in terms of feedback to the signaller. This lack of feedback makes it difficult for the signaller to understand and predict the automation and, hence, creates difficulties for the operator. In addition, the methods for controlling ARS are limited and it can be difficult for the signallers to work cooperatively with the system. Principles of good automation were identified from the literature and recommendations based on these and the findings of the research were developed for future signalling automation systems. These highlighted the importance of improving feedback from ARS and the ability of the signaller to direct the system. It is anticipated that these improvements would allow the signaller and the automation to work more closely together in order to maximise overall system performance. The principles of automation are intended as a generic guidance tool and their application is not confined to rail signalling. There may also be wider implications from the research such as the influence of operators’ ability to understand and predict automation in automation use, and the existence of different types of monitoring behaviour.

Discrete element modelling has been used to capture the essential mechanical features of railway ballast and gain a better understanding of the mechanical behaviour and mechanisms of degradation under monotonic and cyclic loading. A simple procedure has been developed to generate clumps which resemble real ballast particles. The influence of clump shape on the heterogeneous stresses within an aggregate was investigated in box test simulations. More angular clumps lead to greater homogeneity and the interlocking provides a much more realistic load-deformation response. A simple two-ball clump was used with two additional small balls (asperities) bonded at the surface, to represent a single particle; it is shown that particle abrasion gives the correct settlement response. A clump formed from ten balls in a tetrahedral shape was used in monotonic and cyclic triaxial test simulations and found to produce the correct response. The interlocking and breaking of very small asperities which find their way into the voids and carry no load was modelled using weak parallel bonds. The interlocking and fracture of larger asperities was modelled by bonding eight small balls to the ten-ball clump. Monotonic tests were performed on triaxial samples under different confining pressures and the results compared with existing experimental data. Tests were also simulated using uncrushable clumps to highlight the important role of asperity abrasion. Cyclic triaxial tests were then simulated on the same aggregates under a range of stress conditions and the results compared to existing experimental data for the same simulated ballast. The clumps are able to capture the behaviour of ballast under different conditions, and asperity abrasion plays an important role in governing strength and volumetric strain under monotonic loading, and on permanent strains under cyclic loading. The contribution of this thesis is therefore to show that it is possible to model a real granular material under static and cyclic conditions, providing much micro mechanical insight.

Track deterioration has a serious influence on the safety and efficiency (speed restriction) of train operations. Many expensive, disruptive and frequent repair operations are often required to maintain the ballast characteristics due to the problem of settlement. Because of this, a geogrid solution that has proved to be a simple and economical method of reinforcing track ballast is widely used. This project presents an evaluation of the behaviour of geogrid-reinforced railway ballast. Experimental large box pull-out tests were conducted to examine the key parameters influencing the interaction between ballast and the geogrid. The experimental results demonstrated that the triaxial geogrid with triangular apertures outperforms the biaxial geogrid with square apertures and the geogrid aperture size is more influential than rib profile and junction profile. The discrete element method (DEM) has then been used to model the interaction between ballast and geogrid by simulating large box pull-out tests and comparing with experimental results. The DEM simulation results have been shown to provide good predictions of the pull-out resistance and reveal the distribution of contact forces in the geogrid-reinforced ballast system. The discrete element method has also been used to simulate cyclic loading of geogrid-reinforced ballast under confined and unconfined conditions. For the confined condition, box tests have been simulated on unreinforced samples and reinforced samples with different geogrid positions and geogrid apertures. The response of the ballast layer reinforced with geogrid under repeated loading agrees with experimental results. It was found that the optimum location of geogrid is 100 mm depth from base, and the triaxial geogrid outperforms biaxial geogrid. For the unconfined condition, cyclic loading of a trough of ballast has also been simulated, and the sample with the geogrid at 50mm from the sub-ballast layer performs best. It was also found that the used of two geogrids at both 50mm and 150mm from the sub-ballast gave a smaller settlement than using a single layer geogrid, or the unreinforced ballast. The geogrid reinforcement limits the lateral displacement in reinforced zone, which is approximately 50mm above and below the geogrid. Previous investigations have shown that the abrupt stiffness change in track support is often associated with accelerated rates of deterioration of track geometry, high maintenance demand, and poor ride quality. However, at present, there is no detailed understanding of the mechanisms of track geometry deterioration at transition zones. This work provides insight into the factors that can cause or accelerate track degradation at the transition zones, in order to identify and evaluate appropriate mitigation design. A simple track transition model with dimensions 2.1m x 0.3m x 0.45m was simulated by using PFC3D. In order to identify and evaluate appropriate mitigation methods, two kinds of transition patterns, including a single step change and a multi step-by-step change for subgrade stiffness distribution were tested. The influence of the train direction of travel and speed on the transition were also investigated. In addition, geogrid was used in the ballast layer to examine the effects of geogrid reinforcement.

Dissertation for the degree of Master of Science University of the Witwatersrand Johannesburg. April 2013 / Many academic works in the train scheduling environment concentrate on optimizing movements of resources through the physical network. To opti- mize bulk freight lines, algorithms must provide a feasible schedule given the available resources, basic operational constraints and varying demand while ensuring resource allocations that minimise total cost. To be usable the al- gorithm must run within reasonable time limits. This dissertation focuses on the bulk freight train scheduling problem of full loads without track conges- tion but extends to cover operational constraints as well as exible resource allocation and hubs. A problem outline is given wherein the constraints and decision variables are well de ned followed by a review of current literature. An exact formation of the problem is given with benchmarking on small data sets. A genetic algorithm is used to solve for schedules on larger problem data sets. The algorithm was successfully implemented on the 60Mt Coal Line in South Africa which provided notable improvements in e ciencies. Discussion and results are provided.

Railways are integral to the transportation system of a growing economy. There is a constant demand by numerous stakeholders of the railway industry for greater train operational speeds, tonnage, passenger comfort and safety with minimal service disruptions. This is partly achievable through the improvement of the main components of railway track. A fundamental requirement for any railway track is to be able to maintain its as-built geometry over its service life. Settlement of a ballasted railway track is mainly caused by cyclic loading due to the passage of traffic. To return the rail track to the as-built alignment and level, track maintenance needs to be carried out. Tamping is one of the most common and traditional ways of maintaining the track and is not only costly but causes interruption to the day-to-day operations and damages the long term performance of the ballasted track. It therefore remains important to policy makers, rail practitioners and researchers to identify new techniques, innovations or processes that will prolong intervals between scheduled track maintenance. Track settlement is influenced by several interrelated track variables, not least of which are the railway sleeper, ballast and ballast-sleeper interface that have potential for alteration to be optimised with respect to the track performance. In this research, results are presented from a parametric experimental study using three different apparatus namely box test (confined), Composite Element Test (CET) (semi-confined), and Railway Test Facility (RTF) (full-scale), to investigate performance of different sleeper and ballast configurations. The box test and the CET apparatus were used ahead of the RTF (full-scale) apparatus as preliminary tests to obtain an insight into the performance and potential benefits of different sleeper types with and without the use of Under Sleeper Pads (USPs). The aforementioned apparatus were also used for comparison with the full-scale apparatus to assess the consistency of the sleeper settlement results (phase 1 tests). The purpose of using the box test and CET apparatus was also to allow a relatively large number of simplified tests to be carried out on sleeper and ballast combinations (Phase 2 tests) within a reasonable cost and time frame. Phase 2 tests were designed and conducted with consideration of the phase 1 test results. The test results from phase 1 showed that increasing the number of contact points between ballast particles and sleeper, and increasing the coefficient of friction at ballast-sleeper interface improved the settlement performance of the tarckbed. Therefore, having this in mind, further tests were designed and conducted including: finer ballast grading, two-layered ballast systems, frictional sleepers and USPs, and USP types with various stiffnesses. In addition, further tests on ballast bonding/gluing and ballast reinforcement were conducted with the aim of investigating possible ways of minimising ballast bed deterioration. Application of ballast gluing was proven beneficial (in literature) in improving ballast bed performance, however, the overall cost of super glues used for this method was high. Therefore in this study, a low cost glue was introduced and its performance was tested under conditions similar to real track. With regard to ballast reinforcement, the expanded polystyrene was added to the ballast sample with the aim of decreasing the contact forces between ballast particles and consequently minimising ballast bed deterioration and settlement. The observations in this study sought to establish qualitative and quantitative data on the effects of different parameters on the track performance, which may lead to a longer service life with less maintenance. The results showed that the type of sleeper has an influence on the performance of a railway track. With respect to settlement performance of a railway track, sleepers with higher depth and width, coefficient friction, and bending stiffness performed better. Out of all investigated sleeper types without any additional interventions, concrete mono-block gave the least settlement and the plastic sleeper gave the most. It was also found that inclusion of USPs (regardless of type) can be beneficial compared to the ‘no USP’ scenario in: (1) Increasing trackbed resiliency. (2) Reducing maintenance works related to settlement. (3) Reducing sleeper deflections (hogging) at the middle of sleeper. (4) Reducing the rate of deterioration of sleeper support at the rail seat (6) Reducing differences in the performance of different sleeper types. (7) Reducing tendency towards centre binding. (8) Reducing transmitted pressure on subgrade. (9) Making the trackbed stiffness more uniform. The conclusion of research was that use of concrete mono-block sleeper, USPs, finer ballast grading, a two-layered ballast system with finer ballast grading on top, frictional sleeper, frictional USP, and ballast gluing all have potential to improve the performance of ballasted railway track and reduce the maintenance requirements.