Abstract
Past research works on monotonic and cyclic shear behavior of natural silts at the University of British Columbia (UBC), Canada, has shown that the soil fabric and microstructure has a significant influence on the mechanical response of natural silts. With this background, a research program has been undertaken at UBC to capture non-destructive 3D images of Fraser River low-plastic silt using X-ray micro-computed tomography (X-ray µ-CT) for assessing particle fabric. In this regard, identifying individual grains to analyze the particle size distribution (PSD) of a given soil specimen forms a vital step in studying the fabric of silts.
Advancements in computing power have allowed for 3D X-ray imaging of fine-grained soil (silt) specimens. Through computer processing of these 3D images, it is possible to obtain the main dimensional and directional parameters to represent individual particles in digital form; in turn, some of this information can be used to obtain a digital PSD of a given silt matrix. A good way to assess the outcomes of the image processing approach is by comparing the PSDs from the image-based analysis to those from mechanical methods and laser technologies.
In the present work, specimens from a natural silt are analyzed using laboratory methods (i.e., mechanical sieve along with hydrometer analysis) and laser diffraction techniques to establish the benchmark PSDs, and the results are compared with those digitally derived from X-ray µ-CT imaging. In addition, the digital PSDs obtained by imaging of specimens made of pre-calibrated standard-size silica-based beads were also compared with their counterpart physical PSDs. The observed good agreement between the results obtained from physical and digital techniques support the suitability of using the X-ray µ-CT to understand the particulate fabric of silty soils.
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Acknowledgements
The authors would like to acknowledge the financial support of the Natural Science and Engineering Research Council of Canada (NSERC). The collaborative support provided by Dr. Mark Martinez and Mr. James Drummond at the X-ray μ-CT imaging facility at the Pulp and Paper Centre at UBC in Vancouver is deeply appreciated. Thanks are due to Carlo Corrales for his support in the sample preparation and laboratory testing performed for this research as an undergraduate research assistant.
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Valverde Sancho, A.M., Wijewickreme, D. (2022). Digital Particle Size Distribution for Fabric Quantification Using X-ray μ-CT Imaging. In: Wang, L., Zhang, JM., Wang, R. (eds) Proceedings of the 4th International Conference on Performance Based Design in Earthquake Geotechnical Engineering (Bei**g 2022). PBD-IV 2022. Geotechnical, Geological and Earthquake Engineering, vol 52. Springer, Cham. https://doi.org/10.1007/978-3-031-11898-2_206
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