Generation of dense granular deposits for porosity analysis: assessment and application of large-scale non-smooth granular dynamics

8Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The knowledge of structural properties of granular materials such as porosity is highly important in many application-oriented and scientific fields. In this paper we present new results of computer-based packing simulations where we use the non-smooth granular dynamics (NSGD) method to simulate gravitational random dense packing of spherical particles with various particle size distributions and two types of depositional conditions. A bin packing scenario was used to compare simulation results to laboratory porosity measurements and to quantify the sensitivity of the NSGD regarding critical simulation parameters such as time step size. The results of the bin packing simulations agree well with laboratory measurements across all particle size distributions with all absolute errors below 1%. A large-scale packing scenario with periodic side walls was used to simulate the packing of up to 855,600 spherical particles with various particle size distributions (PSD). Simulation outcomes are used to quantify the effect of particle-domain-size ratio on the packing compaction. A simple correction model, based on the coordination number, is employed to compensate for this effect on the porosity and to determine the relationship between PSD and porosity. Promising accuracy and stability results paired with excellent computational performance recommend the application of NSGD for large-scale packing simulations, e.g. to further enhance the generation of representative granular deposits.

Cite

CITATION STYLE

APA

Schruff, T., Liang, R., Rüde, U., Schüttrumpf, H., & Frings, R. M. (2018). Generation of dense granular deposits for porosity analysis: assessment and application of large-scale non-smooth granular dynamics. Computational Particle Mechanics, 5(1), 59–70. https://doi.org/10.1007/s40571-016-0153-0

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free