Evaluating the sensitivity of low-frequency ground-penetrating radar attributes to estimate ballast fines in the presence of variable track foundations through simulation

Abstract

The sensitivity of three low-frequency (<1 GHz) ground-penetrating radar attributes commonly used to infer the amount of fines present within railway ballast was evaluated using synthetic datasets. Variations in ballast thickness, saturation, and subballast material type are not often considered during laboratory or small-scale (few kilometres of track) field studies. If ground-penetrating radar were to be applied as a ballast degradation detection tool on a subdivision (hundreds of kilometres) scale, it is critical to assess the impact variations these track foundation conditions will have on the inferred amount of fines present within the ballast. In this analysis, a two-layer (ballast and subballast) track foundation model was incorporated into a series of ground-penetrating radar simulations where the physical dimensions and electromagnetic properties of the model were systematically varied. It was through the electromagnetic properties that the volumetric amount of fines and moisture present within the ballast and the type of subballast material were altered. The ground-penetrating radar response of each model was simulated using a finite-difference time-domain solver for Maxwell’s equations (gprMax). The amount of fines present in the ballast was then inferred through attributes calculated from the synthetic ground-penetrating radar measurements and related to the known model input. This comparison revealed that ambiguities in the ground-penetrating radar attribute amplitudes were common. Specific ground-penetrating radar attribute amplitudes could not be uniquely associated with the known amounts of fines present within the ballast as the other conditions in the track foundation (ballast saturation, ballast thickness, and subballast material) were varied. As such, a quantitative and reliable estimation for the amount of fines present within ballast using ground-penetrating radar measurements over large scales would be difficult without first constraining the variability in the track foundation.

Keywords

Ground-penetrating radar ballast degradation data simulation attributes railways

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