4.6 Article

An algorithm for generating mechanically sound sphere packings in geological models

Journal

COMPUTATIONAL PARTICLE MECHANICS
Volume 8, Issue 2, Pages 201-214

Publisher

SPRINGER INT PUBL AG
DOI: 10.1007/s40571-020-00324-7

Keywords

Sphere packings; Adaptive refinement; Geological models; Discrete element method

Funding

  1. RING-GOCAD Consortium

Ask authors/readers for more resources

The discrete element method (DEM) is a powerful tool for simulating complex mechanical behaviors by discretizing the targeted medium with particles. The properties of particle assemblies used in DEM simulations directly impact the behavior of the simulated medium. Generating particle assemblies to avoid bias induced by their fabric and conforming with the structural discontinuities of the medium is critical for accurate simulations.
The discrete element method (DEM) is a powerful tool for simulating complex mechanical behaviors which discretizes the targeted medium with particles. The properties of particle assemblies used in DEM simulations directly impact the behavior of the simulated medium. It is thus of critical importance to generate particle assemblies so as to (1) avoid any bias induced by their fabric and (2) conform with the structural discontinuities of the medium under consideration. The main objective of this work is to propose an algorithm, inspired by the space-filling Apollony fractal, to generate sphere packings in geological objects as a first step toward their mechanical modeling with the DEM. In particular, we assess the relevance of the generated packings for simulating the behavior of a rocklike material, and we discuss the ability of the proposed approach to discretize geological models. The algorithm ensures the tangential conformity of spheres with the model boundaries internal and external, and enables to adapt the particle size distribution in the vicinity of structures of interest such as fractures or faults.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available