Development and application of the Illinois Buckle Risk Model (IBRM) using multi-source track condition data

Abstract

Track buckles occur more frequently in Continuously Welded Rail (CWR) as they lack joints to accommodate axial thermal expansion. Analysis of Federal Railroad Administration (FRA) accident database reveals that buckled-track derailments have been a persistent safety concern for U.S. railroads. The FRA initiated an extensive research program in the 1980's to develop and experimentally verify a dynamic buckling theory which culminated in the development of the CWR-SAFE software. The Buckle module of CWR-SAFE accepts quantitative track condition input parameters and assesses the buckling risk of track in terms of its Buckling Safety Margin (BSM). BSM is a composite metric that accounts for track strength, rail temperature, and rail neutral temperature.

Since the development of CWR-SAFE, there have been notable advancements in track inspection technologies capable of providing high-resolution track health data. The Illinois Buckle Risk Model (IBRM) leverages the outputs from three-dimensional machine vision and track geometry measurements systems into the CWR-SAFE environment to perform buckle risk assessment at an individual crosstie resolution. IBRM uses results from field and laboratory experiments to calibrate inspection system outputs into quantified inputs for CWR-SAFE. The application of IBRM is demonstrated using data collected from a Class I railroad subdivision. BSM calculations show that 1.9% of the subdivision track is in the desired range, 95.7% is in the adequate range, and 2.4% is in the minimum required range. This information can be used to prioritize both capital renewal projects and maintenance interventions. Results also demonstrate the IBRM’s flexibility and scalability for buckle risk assessment.