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Swedish and other European governments invest significant resources in railroad infrastructure, including maintenance and construction. The degradation of track ballast layers is one of the most critical maintenance issues. Hence, it is of significant interest for infrastructure owners to find novel solutions to mitigate the problem by improving design and maintenance operations. However, established tools for the simulation of railroad systems typically consider the ballast as a solid continuum structure, while in practice, the discrete nature of the particle assembly has to be accurately represented in the model. The sleepers and rails must be modelled as solid structures, which results in the complex coupled problem of combining particulate and structural analysis models. In this paper, the simulation of railroad infrastructure with the example of a transition zone is performed with an explicit surface coupling algorithm of the Discrete Element Method (DEM) and the Finite Element Method (FEM). The ballast layer is represented by individual particles in DEM, where the computations are performed on the GPU. This study focuses on the comparison between a convex and a non-convex particle shape. The rail system with sleepers and the subground with varying stiffness is modelled with solid structures in FEM. Properties of the ballast bed, such as the particle shape, are found to have a significant impact on the stiffness within the bed and the deflection of the sleepers and rails. Furthermore, the sudden transition from low to high stiffness causes a peak in tensile stress in the subground. The results show that accurate particle shape representation and high computational performance are critical aspects of achieving predictions on a relevant scale. Studying the ballast layer as a particulate system provides a new perspective on dynamics in tracked ballast structures.
Published on 23/11/23
Submitted on 23/11/23
Volume Coupled Approaches Between Particle and Continuum Methods for Solids Mechanics and Fluid-Structure Interaction Problems, 2023
DOI: 10.23967/c.particles.2023.008
Licence: CC BY-NC-SA license
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