It is well-known that track buckling is one of the most commonplace causes of train derailments [FRA 2022]. Accordingly, with partial funding provided by our previous USDOT UTC and the Technology Transportation Center, Inc. (TTCI, now MxV Rail), we are continuing to develop a track buckling model for deployment by MxV Rail as a tool for predicting track buckling [Allen and Fry (2016), Allen, Fry and Davis (2016), Allen and Fry (2017a), Allen and Fry (2017b), Allen and Fry (2017c), Musu, Allen and Cordes ( 2021), Musu and Allen (2023)]. A significant advancement over currently deployed track buckling models, our technology includes an open-source nonlinear finite element algorithm that is user-friendly. Briefly, our track buckling model accounts for the effects of the following on track buckling: both longitudinal and lateral track walk; rail neutral temperature (RNT); both lateral and longitudinal crosstie-aggregate interfacial friction; track modulus; nonlinear track liftoff; and broken spikes. In addition, it is sufficiently robust to be capable for additional environmental causes to be described herein and in a companion proposal. Given these advanced capabilities, track engineers will be able to dramatically improve track safety.
We are informed by our counterparts within the U.S. rail industry that track sometimes buckles on curves. Accordingly, we have utilized our algorithm to model the effect of lateral track walk on buckling resistance of rails, and the effects are pronounced even for small amounts of track walk. On the basis of this, we expect that buckling loads will be significantly reduced on curved track, and this will require a modification of our current Beta-version track buckling algorithm. This project will be undertaken as a means of increasing the robustness of the current track buckling model.