The maintenance of railway systems is critical for their safe operation. However some landscape geographical features force the track line to have sharp curves with small radii. Sharp curves are known to be the main source of wheel flange wear. The reduction of wheel flange thickness to an extreme level increases the probability of train accidents. To avoid the unsafe operation of a rail vehicle, it is important to stay continuously up to date on the status of the wheel flange thickness dimensions by using precise and accurate measurement tools. The wheel wear measurement tools that are based on laser and vision technology are quite expensive to implement in railway lines of developing countries. Alternatively significant measurement errors can result from using imprecise measurement tools such as the hand tools, which are currently utilized by the railway companies such as Addis Ababa Light Rail Transit Service (AALRTS). Thus, the objective of this research is to propose and test a new measurement tool that uses an inductive displacement sensor. The proposed system works in both static and dynamic state of the railway vehicle and it is able to save the historical records of the wheel flange thickness for further analysis. The measurement system is fixed on the bogie frame. The fixture was designed using dimensions of the bogie and wheelset structure of the trains currently used by AALRTS. Laboratory experiments and computer simulations for of the electronic system were carried out to assess the feasibility of the data acquisition and analysis method. The noises and unwanted signals due to the dynamics of the system are filtered out from the sensor readings. The results show that the implementation of the proposed measurement system can accurately measure the wheel flange wear. Also, the faulty track section can be identified using the system recorded data and the operational control center data.

Stochastic optimal control is an important area of research in engineering systems that undergo disturbances such as earthquake excitations and blast waves. Controlling states such as positions of different parts in these systems is critical in situations in which the system has to operate within limited range of its states. The present investigation is concerned with the application of the stochastic optimal control strategy developed by To (2010) and its implementation as well as providing computed results of linear systems under nonstationary random excitations. In the strategy the feedback matrix is designed based on the achievement of the objectives for individual states in the system through the application of the Lyapunov equation of the system. Every diagonal element in the gain or associated gain matrix is related to the corresponding states. The strategy is applied to two two-degree-of-freedom (dof) systems representing buildings under earthquake excitations. Optimally controlled nonstationary random displacements were obtained by the proposed method and presented in this paper. The computed results include the time-dependent elements of the associated gain matrix. Three-dimensional (3D) graphical representations of the optimally controlled largest peaks of mean squares of displacements and velocities against elements of the feedback gain matrix were included. The latter 3D presentations are important for the design engineer who needs to choose elements of the gain matrix in order to achieve a specific objective in certain states of the system.

Railroad transportation is very important for the economic growth. The effective maintenance of railroad transportation is a critical factor for its economic sustainability. The high repetitive forces from a moving railcar induce cyclic stresses that lead to bending and potential deterioration of rails due to the initiation and propagation of fatigue cracks. Previous research on the prediction of fatigue life has been done under the assumptions of a uniform track bed and a homogeneous rail. However, the spatial variation of track stiffness is expected to increase the maximum stresses in the rails and, therefore, accelerate the fatigue process. This study is focused on the variations of the track modulus and the impact on fatigue life. The computational procedure is based on several hundreds of finite element models of the rails across a set of crossties chosen from a random ensemble with representative statistical variations. The mean of the track moduli is estimated from the field track deflection dynamic measurement data in comparison with the deflection data from the FE models. A multiaxial fatigue model is used for the estimation of fatigue cycles to crack initiation. The results show that a non-uniform track bed can reduce the fatigue life by up to 100 times in comparison with the behavior expected for a uniform track bed. The results of this study are expected to improve the effective maintenance and scheduling of rail inspection.

The bending of rail due to the repeated loading from railcar wheels is a known source of rail fatigue. If rail stresses are sufficiently high, they can initiate and propagate fatigue cracks after repeated cyclic loading such that they ultimately result in rail failure. Previous analyses of stresses from wheel loads have primarily focused on track beds for which the track stiffness is assumed uniform across a length of many cross-ties. In reality, however, spatial variations of track stiffness are known to exist and are affected by many factors such as the weather. These stiffness variations can lead to stresses that are locally higher than those predicted using models based on uniform average track stiffness alone. The work presented here is focused on the influence of spatial variations of track stiffness along the rail with respect to the maximum stresses generated. A computational model of a rail on a set of cross-ties with a statistically varying stiffness is used to study the maximum stresses generated when the track stiffness is not spatially uniform. The mean and standard deviation of the local track stiffness are varied and the maximum stresses at various positions within the rail are examined. This computational procedure is repeated for an ensemble of local track stiffness profiles to acquire the needed statistics of the corresponding stresses. These stresses are then related to crack initiation and the expected rate of crack propagation relative to the given the statistics of the track stiffness. This work is anticipated to have application for rail maintenance and the scheduling of rail defect inspections.

The aim of this analysis was to model the pantograph - catenary system at static equilibrium and provide analytical solutions by computing the natural frequencies of the system, mode functions, equivalent stiffness of the catenary system and the deflections of the catenary wire as a function of position, time and tensioning force. Furthermore, dynamic analysis was conducted analytically and the results of the dynamic performance were obtained. It was shown that the dynamic response of the catenary system is dependent on the design parameters in which tensioning force is included. It was also shown that low tensioning forces result in high risk of contact loss and increased wave propagation in the catenary wire while high tensioning forces result in increased static stresses in the catenary system. The results in this article can be used to select optimum tensioning forces and design parameters for desired pantograph-catenary dynamic performance.