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DEM modelling of railway ballast using the Conical Damage Model: a comprehensive parametrisation strategy
Bettina Suhr1, William A Skipper2, Roger Lewis2
1Virtual Vehicle Research GmbH, Inffeldgasse 21/A, 8010 Graz, Austria.
Granular Matter
|February 7, 2022
Summary
Parametrizing discrete element method (DEM) models for railway ballast is complex. This study introduces a new strategy using the Conical Damage Model (CDM) to improve DEM simulations and reduce computational effort.
Area of Science:
- Computational Geomechanics
- Discrete Element Method (DEM) Modeling
- Granular Material Simulation
Background:
- Parametrizing discrete element method (DEM) models for granular materials like railway ballast is challenging due to dependencies on particle shape, contact laws, and application specifics.
- Previous DEM modeling of railway ballast achieved good agreement with experimental data only when using the Conical Damage Model (CDM), which accounts for physical effects like edge breakage, unlike simpler laws (Cundall-Strack, Hertz-Mindlin).
- Limited understanding exists regarding the influence of CDM parameters and potential ambiguities, hindering reliable DEM model parametrization, especially with varying particle shapes.
Purpose of the Study:
- To investigate the influence of Conical Damage Model (CDM) parameters on discrete element method (DEM) simulation results for railway ballast.
- To address parameter ambiguities within the CDM for DEM models.
- To develop and test a computationally efficient parametrization strategy for DEM models, applicable to different particle shapes.
Main Methods:
- Investigation of a DEM model for railway ballast using a simple particle shape to analyze CDM parameter influence and ambiguities.
- Development of a parametrization strategy designed for reduced computational effort.
- Testing the proposed parametrization strategy using a second, different particle shape.
Main Results:
- Detailed analysis of CDM parameter influence and potential ambiguities in DEM simulations of railway ballast.
- Formulation of a novel parametrization strategy that reduces computational demands.
- Successful testing of the new strategy with a distinct particle shape, demonstrating its broader applicability.
Conclusions:
- The study provides crucial insights into CDM parameter behavior and ambiguities in DEM simulations of granular materials.
- A new, computationally efficient parametrization strategy for DEM models has been developed and validated.
- The presented strategy offers a pathway for calibrating diverse DEM models and investigating particle shape effects in future research.
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