DEM simulation data containing micro- and macro-scale quantities of granular materials under triaxial compression

DOI:10.4121/16632559.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/16632559
Datacite citation style:
Cheng, Hongyang (2021): DEM simulation data containing micro- and macro-scale quantities of granular materials under triaxial compression. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/16632559.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

The database contains the micro scale (raw) simulation data and the postprocessed data at the macro scale. Each dataset is created by a different set of parameter that corresponds to a certain type of soil. Note, only drained triaxial stress paths, starting from an initial void ratio of 0.68 are considered here. The dataset can be recreated using the open-source software Yade (Release version: 2020.01a). The source code that executes the simulation can be found at github.com/chyalexcheng/grainLearning. The database can be used by GrainLearning to find the first estimate of probability distribution of DEM model parameters for calibration and optimization purposes. The micro- and macro-scale data is intended to build data-driven micro-macro transition laws.

History

  • 2021-09-23 first online, published, posted

Publisher

4TU.ResearchData

Format

Raw data (micro-scale) in .yade.gz format Processed data (macro-scale) in .npy format

Organizations

University of Twente, Faculty of Engineering Technology, Department of Civil Engineering

DATA

Files (3)