Discrete element modelling of the effects of particle angularity on the deformation and degradation behaviour of railway ballast
Publication Name
Transportation Geotechnics
Abstract
Railroad ballast exhibits distinct morphological characteristics represented by shape irregularity, corner angularity, and surface texture. Upon repeated train loading, the morphology of ballast undergoes inevitable degradation, particularly in terms of its corner sharpness, which can affect track performance and even pose a substantial threat to operational safety. These aspects have rarely been captured insightfully in most DEM studies on ballast. In contrast, this study examines the influence of particle angularity on the deformation and degradation behaviour of railway ballast upon repeated loading using the discrete element method (DEM). The angularity of ballast particles is captured and quantified using the CT scanning technology in conjunction with an image-based processing strategy, after which the irregularly shaped particles are reconstructed in the DEM. In this numerical procedure, aggregates with varying angularities are created by incorporating a particle degradation subroutine to capture corner abrasion and surface attrition of ballast to mimick real-life field processes. The macro-response of a typical ballasted track subjected to cyclic rail loading is investigated, and the results show that as the angularity increases, the permanent deformation of the track corresponds to a lower permanent strain rate and a higher resilient modulus. However, the opposite behaviour is observed if excessive breakage of the aggregates occurs that reduces the angularity of the individual particles. In this study, detailed microscopic analysis based on DEM in terms of interparticle interaction and associated vibration velocity has also been performed. The results offer distinct clarity to the essential micro-mechanisms embracing particle angularity, and the accompanying influence on the deformation and degradation characteristics of ballast is elucidated with greater insight.
Open Access Status
This publication is not available as open access
Volume
43
Article Number
101154
Funding Number
2023M733118
Funding Sponsor
Australian Research Council