Computational Model for Predicting Lift-Off-Induced Buckling in Rail Structures

A computational algorithm is developed herein specifically for the purpose of efficiently predicting the onset of environmentally induced buckling in rail structures. Particular emphasis is placed on the ability for railway engineers to remotely obtain accurate on-the-fly information regarding the buckling resistance of in-the-field track sections experiencing a wide variety of buckling enhancing environmental conditions. The effects of such conditions considered within the model include (1) both lateral and longitudinal track walk; (2) uneven track structure settlement; (3) mud pumping; (4) ineffective or broken spikes; (5) track lift-off; and (6) nonlinear ballast–crosstie interfacial friction. As such, the algorithm developed herein is envisioned to be remotely accessible by track engineers either by the World Wide Web or a cellphone app. As described in the paper, the model may be considered to be an extension of previous efforts spanning much of the twentieth century, and particularly should be considered as an extension of an existing three-degree-of-freedom model. Building on both previous analytic and computational solutions, a finite-element model is developed for the purpose of predicting buckling as a function of the track and support structure material properties, the track and support system geometries, the applied track loading, and the initial lateral displacement within the track. Particular emphasis is placed on nonlinearity and history dependence of the track environment. The resulting algorithm is deployed herein to solve problems demonstrating usefulness of the model, especially the effects of degradation in track performance on lift-off-induced bucking.