Published January 6, 2022 | Version v1
Dataset Open

Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles under triaxial compresion

  • 1. Université Grenoble Alpes, CNRS, Grenoble INP, 3SR, F-38000 Grenoble, France
  • 2. École Polytechnique Fédérale de Lausanne, Earthquake Engineering and Structural Dynamics, GCB2484, Bâtiment GC, Lausanne, CH-1015, Switzerland

Description

This repository contains the data and processed results of the work "Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles (lentils) under triaxial compression", published in Granular Matter (https://link.springer.com/article/10.1007/s10035-022-01305-8).

The study analyses five triaxial compression tests on cylindrical specimens made up of more than nine thousand lentils. Each specimen is prepared with a characteristic orientation (the orientation of the mould for the deposition of the lentils). Repeated x-ray tomography scanning is performed during deviatoric loading, and each scanned step is reconstructed into a 3D volume. Particles are identified in the first 3D volume (in the form of a labelled image) and tracked from the first image all the way through the test using a novel tracking algorithm, enabling the measurement of particle and contact fabric evolution, as well as strain localisation within the specimens. All the procesing is performed using spam (https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html) software.

 

The Readme.md file contains further details on the experimental campaign, and the structure of the repository. Please refer to the paper "Fabric evolution and strain localisation in inherently anisotropic specimens of anisometric particles under triaxial compression" published on Granular Matter for further details not found on the Readme.md file . Additional information/data not included in this repository is available upon request.

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Additional details

Related works

Funding

European Commission
CALIPER - Creating Granular Materials Experts by Developing Experimental Calibrations for Computational Methods 812638