Assessment of Railway Substructure Integrity using Ground Penetrating Radar

Railway network is one of the main pillars of modern transport systems, offering safety, energy efficiency and a limited environmental footprint. For this reason, great emphasis should be given on assessing the condition and performance of the railway infrastructure, especially after extreme weather events. Νon-destructive testing offers significant advantages in this context, as it enables continuous inspection without disrupting operation. This study presents the results of a Ground Penetrating Radar (GPR) investigation, carried out on a double-track railway line, following severe flood-related impacts. The aim was to assess the condition of the substructure and identify potential critical locations.

GPR surveys were conducted in both traffic directions using a combination of air-coupled and ground-coupled antennas operating at frequencies of 2.0 GHz, 1.0 GHz, and 400 MHz, allowing detailed characterization of ballast, sub-ballast, and underlying subgrade layers’ thickness. Data acquisition was conducted at operational speeds using a rail-mounted vehicle. The collected raw data were processed using signal enhancement and interpretation techniques, such as filtering, time-zero correction, and stratigraphic analysis. The results were calibrated using available geotechnical information from trial pits and dynamic cone penetration (DCP) tests.

The analysis provided continuous layer thickness estimates at 10 m intervals, revealing both overall structure and local irregularities along the line. While ballast thicknesses were generally consistent (53-59 cm), greater variability was observed in the sub-ballast and subgrade layers, with coefficients of variation exceeding 15-20% in particular sections. Several locations showed abrupt thickness reductions, disrupted stratigraphy, and signal attenuation, and were characterized as potentially critical zones.

The findings confirm that GPR can be effectively used as a non-destructive tool for railway infrastructure assessment, particularly in post-event conditions. The approach supports resilience-oriented asset management by allowing early detection of subsurface anomalies without service disruption and contributing prioritize targeted interventions for sustainable maintenance, and log-term infrastructure safety and performance.