At present, high speed dual purpose rail/road vehicles employing fixed non-destructive testing (NDT) sensors are used to inspect rails. Due to the uncertainties in characterisation of the defects when they are detected at high speed, manual re-visiting of the defects by expert operators is required before any decision regarding track maintenance is made. This research has been driven by a desire from the rail industry for a robotic system performing faster than human operators and being capable to both detect and characterise rolling contact fatigue (RCF) cracks in rails with the aim of automating the existing manual inspection and enhancing its accuracy and reliability. This thesis combines expert systems technologies with robotic NDT to fulfil this aspiration. A great deal of effort has been spent to develop a robotic inspection trolley which can automatically detect and characterise the RCF cracks in rails using an alternating current field measurement (ACFM) sensor. It uses a rule based expert system (RBES) proposed to control the robotic trolley and more importantly process ACFM data for both detecting and sizing defects. The developed system can detect the possible presence of defects in railway tracks at high speed pass (5-20 km/h) and can automatically return to an identified defect location to perform a slower and more detailed scan (up to 20 mm/s) across a rail section to determine the size, depth and number of cracks present in that section.

Rolling contact fatigue (RCF) cracks are a widespread problem that impairs the service life of railway rails and wheels, with an associated high cost of labour and capital expenditure for remediation. Severe RCF cracks cause serious safety issues as they can turn down at a larger propagation angle into the rail potentially leading to a rail break. Rail grinding can effectively eliminate RCF cracks if they are detected when they are small enough to be removed. Alternating current field measurement (ACFM) is one of the electromagnetic (EM) techniques that can be used for defect detection and sizing in the rail industry. ACFM has been reported to be more accurate in providing length and depth information than conventional UT for small RCF cracks and is less sensitive to lift-off than eddy current methods. The aim of the present research is to analyse the response of ACFM signals to single and multiple RCF cracks in railway rails using experimental measurements and FE based modelling tools, focusing on the influences of crack vertical angle and multiple cracks (number, spacing, size, uniformity) on the ACFM signal to improve the accuracy of dimension predictions. A novel method (using the Bz signal) is proposed to determine the vertical angle of the RCF cracks, which then allows the crack vertical depth to be determined from the pocket length (standard output from ACFM measurements) and therefore the appropriate amount of rail grinding to remove the RCF cracks. It was found that the vertical angle influences the pocket length determined from the measured ΔBxmax/Bx value when the cracks are shallow (vertical angles < 30°), therefore greater accuracy can be obtained when compensating the ΔBxmax/Bx value using the determined vertical angle. It is shown that the variations of crack surface length, crack inner spacing and crack number for multiple cracks also influence the ΔBxmax/Bx values determined for multiple cracks. The influences of asymmetrical crack shapes on crack sizing are discussed, in general it has been found that for accurate sizing of RCF cracks using a single ACFM scan the cracks should be regular, where the assumption of semi ellipse shapes is appropriate. The methods developed in the project were assessed using calibration samples (machined cracks with different sizes and vertical angles) and rails removed from service containing single and multiple RCF cracks. It was found that the new approach proposed in this work allowed the vertical angle to be predicted well for single and multiple RCF cracks (difference to measurements < 14.3 %). In addition the error in pocket length prediction is greatly decreased when using the sizing method including compensation determined from the crack vertical angle.

Railway tracks deteriorate over time due to the combined effects of train loads and environment. To carry out appropriate maintenance, it is necessary to measure the condition of the track. There are two broad categories of condition measures namely: function and structural measures of conditions. Functional measures of condition assess the condition of the track from the point of view of the user. An example of a commonly used functional measure of condition is track geometry. In the UK, track geometry is measured by the track recording coach and it is carried frequently on the entire network. On the other hand, structural measures of condition assess the structural integrity of the track. Example of a commonly used structural measure of condition is track stiffness. In the UK, track stiffness is measured using the Falling Weight Deflectometer (FWD) and it is carried out less frequently on specific railway track sections as it is very slow, requires closure of the track and is expensive to operate. The aim of this research is to investigate the feasibility of using track geometry measurement to extract track stiffness information and ultimately develop a prototype automated system to achieve this.

The writer analyses the introduction of a simulator enabled approach to railway traction driver training and assesses whether the transition from a conventional training delivery process has been effective. The evaluation of effectiveness is based on a study of Iarnród Éireann’s simulator system. Evidence is contained within four supporting strands, i.e., the change in relevant operational risk that has been calculated using ex ante and ex post runs of Iarnród Éireann’s risk model, the internal rate of return on the financial investment necessary to effect the change, the results of an operator attitudinal study and the findings of an independent expert audit. The study establishes that simulation is an effective training medium. The attributes of the system and the use cases that resulted in this finding are described. The writer also presents additional value-adding training objectives that could increase the project’s internal rate of return or IRR. The study affirms that the required verisimilitude of a simulator system is a function of the training goals and the nature of the skills under development. Design features and use strategies can mitigate for potential negative effects of simulator operation. The findings have industry-wide relevance for those tasked with providing effective training to the 133,000 train drivers within the European Union.

Improvements in railway capabilities have resulted in heavier axle loads and higher speed operations, which increase the dynamic loads on the track. As a result, railway subsidence has become a threat to good railway performance and safe railway operation. The author of this thesis provides an approach for railway performance assessment through the monitoring and prediction of railway subsidence. The InSAR technique, which is able to monitor railway subsidence over a large area and long time period, was selected for railway subsidence monitoring. Future trends of railway subsidence should also be predicted using subsidence prediction models based on the time series deformation records obtained by InSAR. Three time series prediction models, which are the ARMA model, a neural network model and the grey model, are adopted in this thesis. Two case studies which monitor and predict the subsidence of the HS1 route were carried out to assess the performance of HS1. The case studies demonstrate that except for some areas with potential subsidence, no large scale subsidence has occurred on HS1 and the line is still stable after its 10 years' operation. In addition, the neural network model has the best performance in predicting the subsidence of HS1.

Complex optimisation problems, which are concerned with optimising a given aspect of a complex system, such as time or energy, are difficult to solve. Often a range of solutions exist, and the difficulty lies in determining which solutions to implement in which part of the system. Within this work, a novel method is developed that allows the solver to overcome the key challenges for these types of problems, which are: defining the system parts (subsystems); minimising model complexity; quantifying solution effectiveness; and identifying relationships between solutions and subsystems. The method is demonstrated through application to the problem of railway traction energy saving. Subsystems are defined using quantified network and service characteristics. For each subsystem, the trends between six key solutions and the key performance indicators are analysed using multivariate data analysis and visualisation techniques. The relationships between subsystems are then explored at system level. The analysis determines the suitable solutions for each type of railway, providing information for operators about which solutions to target. Based on the results, the implementation of permanent magnet motor technology is considered, illustrating that the method is a suitable tool for informing further studies.

The profound value of wayside monitoring in helping safeguard the RAMS of railway operations is undeniable. However, despite significant investments by the rail industry, the efficiency and reliability of wayside monitoring have not reached the desired level. Structural deterioration of the rail infrastructure and rolling stock faults still remain a significant problem which needs to be addressed as traffic density, train speeds and axle loads increase in rail networks around the world. The main objectives of this study were to develop and evaluate an advanced wayside monitoring system based on acoustic emission and vibration analysis that can detect various types of axle bearing defects in rolling stock and structural deterioration in cast manganese crossings. The potential architecture for different levels of system correlation has been proposed which can be further integrated with customised monitoring system. A novel signal processing technique based on spectral coherence has been developed. This particular method is based on the identification of suitable templates containing features of interest. It also features in identifying the severity of the defect. In addition, a suitable approach for data fusion from various sensors has been investigated. Successful tests have been carried out under simulated conditions and in the UK network.

The effort here, compiled over a nearly three-year period, is simply to encourage reporters of the mass media, those recorders of instant history on a daily basis, to take the time to put down in print somewhere the memories of old-timers everywhere. While centered in Corinne, Utah, the last rabble-rousing boomtown along the first transcontinental railroad to span the United States, this work is a collection of feature articles, laced with anecdotes and perhaps tall tales, of the type old-timers are eager to tell. It is a renegade mixture of oral and written histories and probably breaks most of the rules of structures research, but it attempts to add a little color, a little life, between the cold letters chiseled into cemetery headstones. If these stories are not put down for generations yet to come to read, to ponder and possibly to enjoy, they will be buried -- quite literally -- forever. Whether these stories are true or have been "blossomed" by retelling over the years is not the question here. Such stories add a perspective, and may haps a better understanding, to the dusty and often dry dates recited by children in elementary school. In this regard, these children will grow up, wed and work, and they will have their stories to tell, hopefully before they, too, die.

Thesis (M.S.)--University of Illinois, 1942. / Reproduced from typewritten copy. Bibliography: leaves 128-131.

The development of the large corporate railroad systems in the Midwest, during the late nineteenth and early twentieth centuries, produced many high quality, architecturally significant railroad stations. Among these, Richmond's Pennsylvania Railroad Station, built to the designs of the D.H. Burnham & Co., of Chicago in 1902-1903, is a fine example of the Beaux-Arts and Neo-Classical Revival Styles of architecture popular after the Columbian World Exposition of 1893. The Richmond station remains as the last example of the Burnham Co.'s railroad station work in Indiana. This thesis will review the history and current status of the station, review and summarize the field of railroad station reuse, and present an adaptive reuse plan for the station. / Department of Architecture