Understanding track substructure behavior: Field instrumentation data analysis and development of numerical models

Abstract

Numerous studies have targeted using numerical modeling, field instrumentation, or combinations of both to gain insight into track substructure behavior under loading. In-depth understanding of track substructure behavior serving both passenger and freight trains is critical to developing suitable design and maintenance/rehabilitation methods to ensure adequate performance under loading. This manuscript presents findings from a recently completed study involving advanced instrumentation and numerical modeling to investigate track substructure-related issues at several problematic railroad bridge approaches in the United States. Multi-Depth Deflectometers (MDDs) were installed to measure transient as well as plastic deformations experienced by track substructure layers under loading. Strain gauges were installed on the rail web to measure the vertical wheel loads applied during train passage. Data from the field instrumentation was used to make inferences regarding the relative contributions of different substructure layers towards the differential movement problem. A 3-D Finite Element (FE) model was developed to further understand the behavior of the instrumented locations, and was calibrated using the field instrumentation data. An elastic layered track analysis program, GEOTRACK, was first used to iteratively backcalculate individual track substructure layer moduli from the field measurements; these backcalculated modulus values were subsequently used in the FE model to predict track response under transient loading conditions. Modulus values estimated for the ballast layer were found to be significantly affected by the presence of gaps at the tie-ballast interface at track transitions. Once validated, the model was further modified to match transient displacement results acquired in the field using a quasi-static moving load approach. Good agreement was found between the model predictions and field instrumentation results. Development of advanced numerical models augmented by field instrumentation data can facilitate the design and maintenance of well-performing track structures.

Modeling the Dynamic Behavior of Track Transitions Along Shared Track Corridors

“…Note that validation of this model was carried out using field instrumentation data collected as part of a research project undertaken at the University of Illinois that focused on investigating different factors contributing to the problem of differential movement at track transitions. Findings from the above-mentioned research project have been presented in multiple manuscript over the past decade (Mishra et al, 2012;Tutumluer et al, 2012;Mishra et al, 2014;Mishra et al, 2016;Tutumluer et al, 2016;Boler et al, 2018;Hou et al, 2021). In-line with the field instrumentation effort, a point lying 18.3-m (60-ft.) away from the bridge abutment was taken to present OTL, whereas a point lying at a distance of 4.6 m (15 ft) from the bridge abutment was taken as being representative of NBL.…”

“…Although detailed discussion of different factors governing poor performance of track transitions is not the primary focus of this manuscript, this aspect has been discussed in great details by the following researchers: Li and Davis (2005), Tutumluer et al (2012), Mishra et al (2014), Mishra et al (2017), and Boler et al (2018). According to Nicks (2009), remedial measures aimed at mitigating the bump problem at railway bridges can be divided into different interrelated categories, such as: 1) reducing approach settlement, 2) decreasing the track modulus on the bridge deck, 3) increasing the modulus of the approach section, 4) reducing ballast wear and movement, and 5) increasing track damping on the bridge deck.…”

Finite Element Modeling of the Dynamic Response of Critical Zones in a Ballasted Railway Track

“…Several researchers have conducted field investigations in the track transitions to understand their behavior and have identified the probable causes of the associated problems (Li and Davis, 2005;Stark and Wilk, 2015;Coelho et al, 2017;Boler et al, 2018;. These investigations revealed that the root cause of the problem needs to be identified before applying an appropriate mitigation measure.…”

Dynamic Behavior in Transition Zones and Long-Term Railway Track Performance

“…Railway tracks are known to show higher degradation rates at transition zones between sections with different characteristics and support conditions, i.e., between embankment and bridges, tunnels, or other structures (ERRI, 1999;Banimahd et al, 2012;Varandas et al, 2014a;Paixão et al, 2013;Boler et al, 2018). These locations often exhibit differential settlements that develop during the life cycle of the track due to multiple structural and geo-mechanical reasons.…”