Issue |
E3S Web Conf.
Volume 92, 2019
7th International Symposium on Deformation Characteristics of Geomaterials (IS-Glasgow 2019)
|
|
---|---|---|
Article Number | 12009 | |
Number of page(s) | 6 | |
Section | Treated Geomaterials: Mechanical Stabilisation | |
DOI | https://doi.org/10.1051/e3sconf/20199212009 | |
Published online | 25 June 2019 |
Understanding the mechanisms of root-reinforcement in soils: soil shear tests using X-ray computed tomography and digital volume correlation
Faculty of Physical Sciences and Engineering, University of Southampton, UK
* Corresponding author: daniel.bull@soton.ac.uk
Soil containing plant roots may be expected to exhibit a greater shearing resistance compared with the same ‘unreinforced’ soil, providing enhanced stability and effective erosion control, particularly for earth slopes. To be able to rely on the improved shearing resistance and stiffness of root-reinforced soils, it is important to understand and quantify the effectiveness of root reinforcement. This requires sophisticated multiscale models, building understanding at different length scales, from individual soil-root interaction through to full soil-profile or slope scale. One of the challenges with multiscale models is ensuring that they are representative of real behaviour, and this requires calibration to detailed high-quality experiments. The focus of the work presented was to capture and quantify root-reinforcement behaviour and associated soil and root deformation mechanisms during direct shear at the macroscopic to millimetre length scales. A novel shear box was developed to operate within a large-scale X-ray computed tomography (CT) scanner. Tests were interrupted to be scanned at a series of shear displacements from 0-20 mm to capture the chronology of behaviour in three-dimensions. Digital volume correlation (DVC) was applied to the CT dataset to obtain full-field 3D displacement and strain component information. The study demonstrates feasibility of the technique and presents preliminary DVC results.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.