4.7 Article

Open-source support toward validating and falsifying discrete mechanics models using synthetic granular materials-Part I: Experimental tests with particles manufactured by a 3D printer

期刊

ACTA GEOTECHNICA
卷 14, 期 4, 页码 923-937

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s11440-018-0703-0

关键词

3D printing; Compression and recompression index; Discrete DIC; Oedometer test; Open-source data for inverse problems; X-ray CT

资金

  1. Earth Materials and Processes program from the US Army Research Office [W911NF-15-1-0442, W911NF-15-1-0581]
  2. Dynamic Materials and Interactions Program from the Air Force Office of Scientific Research [FA9550-17-1-0169]
  3. nuclear energy university program from department of energy [DE-NE0008534]

向作者/读者索取更多资源

This article presents a new test prototype that leverages the 3D printing technique to create artificial particle assembles to provide auxiliary evidences that supports the validation procedure. The prototype test first extracts particle shape features from micro-CT images of a real sand grain and replicates the geometrical features of sand grain using a 3D printer. The quantitative measurements of the particle shape descriptors reveal that the synthetic particles inherit some attributes such as aspect ratio and sparseness of the real materials while exhibiting marked differences for sphericity and convexity. While it is not sufficient to consider the printed particle assembles a replica of the real sand, the repeatable manufacture process provides convention tools to generate additional data that supports the validation procedure for particulate simulations. Oedometric compression tests are conducted on a specimen composed of the printed particles of identical size and shape to create benchmark cases for calibrating and validating discrete element models. Results from digital image correlation on the synthetic sand assemblies reveal that the fracture and fragmentation of the synthetic particles are minor, which in return makes particle position tracking possible. As our prototype test and research data are designed to be open source, the dataset and the prototype work will open doors for modelers to design further controlled experiments using synthetic granular materials such that the individual influence of each morphological feature of granular assemblies (e.g., shape and size distribution, void ratio, fabric orientation) can be individually tested without being simultaneously affected by other variables.

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