Dataset
Data Publication
DEM simulation data containing micro- and macro-scale quantities of granular materials under triaxial compression
Cheng, Hongyang
4TU.ResearchData
(2021)
Descriptions
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.
Keywords
MSL enriched keywords
MSL vocabulary keywords corresponding to originally assigned keywords
Originally assigned keywords
Metadata
MSL enriched sub domains
Resource Type
Source publisher
| 4TU.ResearchData |
Creators
| Cheng, Hongyang |
| Personal |
| 0000-0001-7652-8600 |
Contributors
| University Of Twente, Faculty Of Engineering Technology, Department Of Civil Engineering |
| Organizational |
Citation
Cheng, H. (2021). DEM simulation data containing micro- and macro-scale quantities of granular materials under triaxial compression (Version 1) [Dataset]. 4TU.ResearchData. https://doi.org/10.4121/16632559.V1
References
Dates
| Issued | 2021-09-23 |
Language
- no language entry found -
Rights
| Name | Creative Commons Zero v1.0 Universal |
| URI | https://creativecommons.org/publicdomain/zero/1.0/legalcode |
| Identifier | cc0-1.0 |
| Identifier Scheme | SPDX |
| Scheme URI | https://spdx.org/licenses/ |
Locations
- no geo-locations found -