Optimization of the design of railway infrastructure and its components requires a comprehensive understanding of the loading demands that are expected. Currently, many design guidelines for track components use historical wheel loads and calculate bending moments based on broad assumptions. However, tools are available to accurately quantify and characterize the variability each load has on a particular component. This is particularly important in shared use rail corridors where higher speed passenger services operate on the same infrastructure as heavy axle load (HAL) freight trains. Each traffic type generates unique demand variabilities, and these should be incorporated into a holistic approach to optimized track design. Therefore, researchers at the University of Illinois at Urbana-Champaign (UIUC) are conducting field research aimed at the characterization of field conditions on Amtrak’s Northeast Corridor through the use of wheel impact load detector (WILD) data and concrete crosstie surface strain gauges. Results from this experimentation show high variability of loads resulting from varied types of train operations and significant differences in impact load ratios. Finally, laboratory measured flexural capacity for the concrete crossties showed a conservative design with a potential margin of improvement in reduction of residual capacity (i.e., factor of safety).
Many analytical methods and other processes have been developed for the evaluation of railway track and its components, but these have largely been used for analysis. Design is often driven by development projects that do not engage research, resulting in designs that may not be optimized in the context of the broader track structure. This paper proposes a mechanistic-empirical (M-E) analysis and design framework that encourages an understanding of mechanical load-response behavior and comparison of loading demands, and the capacity of the track infrastructure component under study. The approach builds on similar advancements in the field of highway pavement research, including the development and use of the Mechanistic-Empirical Pavement Design Guide (MEPDG). Rail applications present unique economies to a focused M-E design approach, given that loads are concentrated in localized regions and beneath the rails. This paper first reviews prior design and analysis approaches, then presents the essential features of an M-E railway track system and component analysis and design, and, in the end, notes gaps that will require future research before proper implementation of M-E design within rail engineering. The authors also discuss the role of probabilistic design and structural reliability analysis in future design practices. Finally, governing mechanistic failure modes for the track system as well as components and associated life cycle data to achieve full implementation of such an M-E design process are identified and a path forward for implementation is proposed.
Current structural models used for the flexural design of prestressed concrete sleepers assume that ballast bearing support is static and located within a fixed region. This assumption implies a linear relationship between wheel load and bending moment. However, field data gathered from instrumented sleepers shows that this trend is non-linear, and the difference in flexural behavior between model predictions and field-measured demand is significant. Using back-calculation techniques and the development of a sleeper support analysis tool, this paper investigates the load-dependency of sleeper support condition. It is hypothesized that a given support condition redistributes ballast reaction forces due to the mechanical interaction of ballast particles with the sleeper’s deflected shape. It was found that redistribution of support conditions can reduce the expected flexural bending moment up to 45% when compared with moments calculated using traditional design guidelines. This effect (non-linearity) is greater as wheel loads increase. Results from revenue service field experimentation provided insight into the interaction between sleeper and ballast and serve as a foundation for the development of more complex analytical models. This will facilitate revisions to the future flexural design procedures for concrete sleepers, to ensure they are optimized for their expected service loading conditions.
Continuously welded rail (CWR) has become more popular than bolted joints because of the advantages of continuous geometry and stiffness and the resulting maintenance savings. Due to a variety of reasons, a considerable number of bolted joints are still in service in rail transit systems. With the high frequency of impact loads, rail at bolted joints are vulnerable to defects, such as cracking and head-web separation that could lead to more drastic failures and consequences (i.e. derailments, etc.). To prolong the service life of joint bars and rails, rail-end easements in the center of the bar were proposed and became standard in some freight rail companies. However, the effectiveness of a joint bar easement largely depends on the geometry of the easement. Therefore, the easement designed for freight track may not be effective for rail transit infrastructure. Further, the effect of easement geometry has not been thoroughly investigated and documented. Therefore, this study investigates the stress distribution at the rail end bolt-hole and upper fillet areas for joint bars with different easement geometries through a parametric analysis performed with Finite Element (FE) modeling. The FE model used in this study was developed specifically to study rail joints and was validated through full-scale laboratory testing. Results from this study show that a deeper easement yields lower contact stresses, while a longer easement does not necessarily reduce the contact stresses with the studied combination of rails and bolted joints for transit track. An easement may reduce the service life of the joint if the geometry of the easement is not properly engineered.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.