Effect of Sediment Form and Form Distribution on Porosity: A Simulation Study Based on the Discrete Element Method

TL;DR

This study uses discrete element method simulations validated by experiments to analyze how sediment grain shape affects porosity, leading to a new predictive model based on form ratios and distributions.

Contribution

It introduces a novel simulation approach and a simple, accurate porosity prediction model considering sediment grain form and its distribution.

Findings

Porosity mainly depends on the inverse of the mean equancy.

Shape-related properties are relevant only for small form ratios.

The model accurately predicts porosity using flatness and elongation measurements.

Abstract

Porosity is one of the key properties of dense particle packings like sediment deposits and is influenced by a multitude of grain characteristics such as their size distribution and shape. In the present work, we focus on the form, a specific aspect of the overall shape, of sedimentary grains in order to investigate and quantify its effect on porosity, ultimately deriving novel porosity-prediction models. To this end, we develop a robust and accurate simulation tool based on the discrete element method which we validate against laboratory experiments. Utilizing digital representations of actual sediment from the Rhine river, we first study packings that are composed of particles with a single form. There, the porosity is found to be mainly determined by the inverse equancy, i.e., the ratio of the longest to the smallest form-defining axis. Only for small ratios, additional shape-related properties become relevant, as revealed by a direct comparison to packings of form-equivalent ellipsoids. Since sediment naturally features form mixtures, we extend our simulation tool to study sediment packings with normally-distributed forms. In agreement with our single form studies, the porosity depends primarily on the inverse of the mean equancy. By supplying additional information about a second form factor and the standard deviations, we derive an accurate model for porosity prediction. Due to its simplicity, it can be readily applied to sediment packings for which some measurements of flatness and elongation, the two most common form factors, are available.