An Investigation of the Influence of Random Packing on PFC3D Simulations of Unconfined Compression, Brazilian, and Three-Point Bending Tests
Authors: Haydn-Myer M. , MacLaughlin M. , Arnold L. 
Published: August 2024

ABSTRACT:
In Purdue University's Damage Mechanics Challenge (Jiang et al., 2021), participants used numerical modeling to predict rock crack formation in synthetic material. Purdue researchers provided laboratory data on 3D-printed blocks subjected to unconfined compression, Brazilian, and three-point bending tests. A participating team from Montana Tech and the University of Washington – Tacoma employed multiple methods including the distinct element method (DEM) using Itasca's Particle Flow Code (PFC3D) to simulate the experiments (Johnston, 2023). Although the traditional bonded particle PFC3D models used to predict crack formation provided a close match to the experimental data, the variability observed with repeated physical tests on multiple samples was not captured in the numerical models, which provided a single solution (per test type) for the provided specimen geometries. This paper describes a follow-up study done to investigate the influence of random particle packing on the DEM model results. Using an F-test, the range of peak strength values observed in ten simulations (for each test type) with slightly different packing was found to be similar to Purdue's DMC range of values.

1. BACKGROUND
In 2021, Purdue University posted the benchmark dataset and challenge information for their Damage Mechanics Challenge (DMC). Participants were asked to develop numerical modeling approaches using data provided from three different lab tests for calibration: unconfined compression strength (UCS) tests, Brazilian tests, and center notch three-point bending experiments. The lab tests were conducted on a 3D-printed material so the specimens would be as consistent as possible, free of significant unique flaws, and fail in a controlled manner. Computational numerical models created by the participants aimed to be ‘repeatable and unbiased metrics to quantitatively assess and measure the quality of the theoretical and data-driven models' (Jiang et al., 2021).
This paper describes a follow-up study done to explore simulation variations of models developed by a collective team from Montana Tech and University of Washington – Tacoma. To simulate laboratory experiments, the team employed multiple methods including the distinct element method (DEM) and a hybrid finite-discrete element method. This paper focuses on the DEM simulations using Itasca's Particle Flow Code (PFC3D) employing the traditional bonded-particle ball model approach. The PFC3D modeling results provided a close match to the experimental data. However, the variability observed with repeated physical tests on multiple specimens was not captured in the numerical modeling, which provided a single solution (for each type of laboratory test) for the provided specimen geometries. Previous studies have investigated particle packing in DEM numerical modeling, determining that particle packing has a significant influence on results (e.g. Cundall & Strack, 1979; Potyondy, 2002; Potyondy & Cundall, 2004; Asadi et al., 2012; Ding et al., 2014; Abbireddy & Clayton, 2015; Hoffman et al., 2015; Castro-Filgueira et al., 2017; Ma & Huang, 2018; Harmon et al., 2021; Zhang et al., 2022). Therefore, it was anticipated that some variation would be observed in simulations done using slightly different particle packing.