The rail dynamics modeling package NUCARS has been used extensively to model freight cars. We have found that it can also be used effectively to model freight locomotives. This thesis discusses the development of a NUCARS model to represent a six-axle freight locomotive equipped with steerable trucks. This includes separating it into a set of individual bodies, representing the suspension components as inter-body connections, and validation of the computer model. This model is then used to conduct a study of the impact on tangent track stability and curving performance of varying suspension parameters. It is found that the presence of damping in the system improves hunting stability, while increasing wheel conicity is harmful to stability and varying the flexicoiling stiffness has little effect. In curving, the clearances between the axles and truck frame are very important. Limiting these clearances in the steerable truck causes it to curve similar to a conventional straight locomotive truck and increases both the track force ratios and angles of attack. Increasing the wheel conicity increases an axle's tendency to align with the track and improves the locomotive's curving performance. The lateral stiffness of the inter-axle links and inter-motor links has little effect on the curving of the locomotive. / Master of Science

The design of the freight train truck has gone relatively unchanged over the past 150 years. There has been relatively little change to the fundamental railway truck design because of the challenges of implementing a cost effective and reliable modification to designs that have proven effective in decades of operation. A common U. S. railway truck consists of two sideframes, a bolster, two spring nests, and four friction wedges. The two sideframes sit on the axels. The bolster rides on springs on top of the sideframes. The friction wedges also ride on springs on top of the sideframe, and are positioned between the bolster and sideframe, acting as a damping mechanism. Better understanding the dynamic behavior and forces on the bodies are critical in reducing unnecessary wear on the components, along with potential negative behavior such as loss of productivity and increase in operating costs. This thesis will investigate the dynamic behavior of the truck under warping conditions using a stand-alone model created in Virtual.Lab. This research covers two main areas. First, the full-truck model will be developed and its simulation results will be compared to test data from the Transportation Technology Center, Inc. (TTCI). Data was provided from warp testing performed at the TTCI facilities in the spring of 2008. Once validated, the model will be used to gain a better understanding of the forces and moments that are propagated through the system, and of the dynamics of all bodies. Due to costs and physical constraints, not every bogie component can be instrumented during test, so the computer model will be able to provide valuable information not easily obtained otherwise. Second, full-truck models using different contact geometry between the wedges, sideframes, and bolster will be compared. A model with extremely worn sideframes will allow for investigation into the effects of wear on the damping abilities and warp stiffness of the truck. Another model using split wedges will be compared with the previous model to investigate into the behavior differences in the truck using different types of wedges. By understanding the impact of different geometries on the overall performance of the truck, better decisions on design and maintenance can be made in the future. After creating the models, we found that the full-truck model created in LMS® Virtual.Lab compared well with the test data collected by TTCI. In the comparison with NUCARS® we determined that the stand-alone model, which incorporates the wedges as bodies, captures the warp dynamics of the truck better than NUCARS®, which models the wedges as connections. By creating a model with severely worn sideframes, we were able to determine that the truck loses its abilities to damp bounce in the system as well as to prevent warping when the components become sufficiently worn. The split-wedge model behaved similarly to the standard full-truck model for bounce inputs, but had a significantly different behavior in warp. Further development will be needed on the split-wedge model to be confident that it behaved as expected. / Master of Science

The accuracy of the results from a rail vehicle dynamic model is dependent on the realism of the track input to the model. An important part of the track input is the irregularities that exist on actual track. This study analyzes the irregularities inherent in railroad track geometry data, and provides an analytical method for creating track data with the irregularities for use as the input to a dynamic model. Track data, measured from various classes of track, was examined using statistical and frequency analysis techniques to identify any similarities in the characteristics of the irregularities. The results showed that each class of track had a distinctive value for the standard deviation of the alignment and profile data. It was also determined that the frequency content of all the tracks was contained within a common bandwidth. The track irregularities could then be generated with the same characteristics as an actual track. The method for creating the track irregularities was then programmed into TRAKVU. TRAKVU is a track preprocessor used in conjunction with NUCARS, a railcar dynamic modeling program¹. TRAKVU enables users to create track data and apply the appropriate irregularities so that the track will have the characteristics of the desired class of track. A validation was then performed to determine how well track created in TRAKVU simulated actual tracks. The statistical and frequency characteristics of created tracks were compared directly with actual tracks. Created track was also used as the input to a dynamic model. The predicted vehicle response was then compared to the actual vehicle response and the predicted vehicle response using measured track data as the input. The results from the validation showed that the created track performed as well as the measured track in providing the input to the model. Although the predicted response using the created track did not compare as well with the actual vehicle response, the differences could be attributed to inaccuracies in the model. ¹NUCARS and TRAKVU are copyrighted property of the Association of American Railroads. / Master of Science

The rate at which a railway track deteriorates depends on the response of the track under different static and repeated dynamic forces. These wheel/rail forces lead to imperfections in the rail surface and deviation in track geometry alignment. The wheel/rail forces are dependent upon the quality of maintenance of the characteristics of both train and track. If train components such as wheelsets and suspensions are maintained to a high standard, less dynamic forces are generated at the wheel/rail interface and less damage is caused over time. Therefore, the amount and cost of maintenance of track are reduced. However, there is little known about how the characteristics of train components affect time-dependent track degradation. Track degradation through deviation of track from its ideal position has the most effect on maintenance costs. Therefore, the present research aims to investigate this track degradation and improve understanding of the effects of train characteristics (such as train mass and speed, suspension stiffness and damping) on railway tracks. The research is conducted by looking into the relationship between wheel/rail forces and track degradation on one hand and between wheel/rail forces and train characteristics on the other hand, with the objective of assisting in managing vehicle/track interaction in order to minimise track degradation. This aim is achieved by investigating the above two relationships to attain the desired relationship between track degradation and train characteristics. The research focuses on wheel/rail vertical forces (both amplitudes and frequencies), vertical track alignment (longitudinal vertical profile), and rail head defects. The study started by collecting wheel/rail vertical forces data in addition to data on vertical track degradation under sustained traffic loads on a heavy haul railway section of track in Central Queensland. Also, five years of degradation and maintenance history data were collected on three other test sections of railway track under variety of traffic conditions and loads in Central Queensland. There were four main analyses of this data employed to probe the study. The first analysis was performed by examining the track degradation history data. The standard deviation method was used in this first analysis to acquire the rate of deterioration in terms of its relationship to track profile (roughness). The second analysis was accomplished by correlating the vertical wheel/rail forces to both vertical track profile and rail roughness using signal processing principles and a function know as coherence. The third analysis was carried out by using the computer simulation software NUCARS to obtain the link between wheel/rail forces and the deterioration of the vertical track profile. The fourth analysis was achieved by combining the results obtained from the above three analyses to acquire the rate of track deterioration in terms of its relationship to varying train characteristics. The first analysis mentioned above quantified the relationship between the level of roughness of the track and rate at which that roughness deteriorated. An important outcome of this relationship is that there is a threshold of roughness below which track deterioration is minimal. The track maintenance planners can now use that threshold for cost effective targeting of tamping activities. The correlation study between track roughness and wheel/rail forces using the coherence function found, surprisingly, that the overall deterioration of the track roughness, in the absence of frequencies of forces above 30 Hz, is due to the so-called quasi-static lower frequency oscillations of dynamic forces. This conclusion together with the relationship between vehicle characteristics and track forces, established in the analyses above, has significant implications for the design of wagon bogies and for charges track owners might levy on trains using their tracks. This research is part of a larger Rail CRC project 11/4 called 'Enhancing the Optimisation of Maintenance/Renewal' being carried out in the School of Urban Development in Queensland University of Technology.