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On acquisition parameters and processing techniques for interparticle contact detection in granular packings using synchrotron computed tomography

On acquisition parameters and processing techniques for interparticle contact detection in granular packings using synchrotron computed tomography
On acquisition parameters and processing techniques for interparticle contact detection in granular packings using synchrotron computed tomography

X-ray computed tomography (XCT) is regularly employed in geomechanics to non-destructively measure the solid and pore fractions of soil and rock from reconstructed 3D images. With the increasing availability of high-resolution XCT imaging systems, researchers now seek to measure microfabric parameters such as the number and area of interparticle contacts, which can then be used to inform soil behaviour modelling techniques. However, recent research has evidenced that conventional image processing methods consistently overestimate the number and area of interparticle contacts, mainly due to acquisition-driven image artefacts. The present study seeks to address this issue by systematically assessing the role of XCT acquisition parameters in the accurate detection of interparticle contacts. To this end, synchrotron XCT has been applied to a hexagonal close-packed arrangement of glass pellets with and without a prescribed separation between lattice layers. Different values for the number of projections, exposure time, and rotation range have been evaluated. Conventional global grey value thresholding and novel U-Net segmentation methods have been assessed, followed by local refinements at the presumptive contacts, as per recently proposed contact detection routines. The effect of the different acquisition set-ups and segmentation techniques on contact detection performance is presented and discussed, and optimised workflows are proposed.

computed tomography, contact detection, granular materials, segmentation, soil
2313-433X
Alvarez-Borges, Fernando
5512cdfd-6ad3-475f-8aec-2fc767607314
Ahmed, Sharif
e7181acb-a5ad-4712-b6bd-4c4dfbf6a9dc
Atwood, Robert C.
853929bc-679d-47bb-8ba8-acd139fc857e
Alvarez-Borges, Fernando
5512cdfd-6ad3-475f-8aec-2fc767607314
Ahmed, Sharif
e7181acb-a5ad-4712-b6bd-4c4dfbf6a9dc
Atwood, Robert C.
853929bc-679d-47bb-8ba8-acd139fc857e

Alvarez-Borges, Fernando, Ahmed, Sharif and Atwood, Robert C. (2022) On acquisition parameters and processing techniques for interparticle contact detection in granular packings using synchrotron computed tomography. Journal of Imaging, 8 (5), [135]. (doi:10.3390/jimaging8050135).

Record type: Article

Abstract

X-ray computed tomography (XCT) is regularly employed in geomechanics to non-destructively measure the solid and pore fractions of soil and rock from reconstructed 3D images. With the increasing availability of high-resolution XCT imaging systems, researchers now seek to measure microfabric parameters such as the number and area of interparticle contacts, which can then be used to inform soil behaviour modelling techniques. However, recent research has evidenced that conventional image processing methods consistently overestimate the number and area of interparticle contacts, mainly due to acquisition-driven image artefacts. The present study seeks to address this issue by systematically assessing the role of XCT acquisition parameters in the accurate detection of interparticle contacts. To this end, synchrotron XCT has been applied to a hexagonal close-packed arrangement of glass pellets with and without a prescribed separation between lattice layers. Different values for the number of projections, exposure time, and rotation range have been evaluated. Conventional global grey value thresholding and novel U-Net segmentation methods have been assessed, followed by local refinements at the presumptive contacts, as per recently proposed contact detection routines. The effect of the different acquisition set-ups and segmentation techniques on contact detection performance is presented and discussed, and optimised workflows are proposed.

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Accepted/In Press date: 5 May 2022
Published date: 12 May 2022
Keywords: computed tomography, contact detection, granular materials, segmentation, soil

Identifiers

Local EPrints ID: 468296
URI: http://eprints.soton.ac.uk/id/eprint/468296
ISSN: 2313-433X
PURE UUID: de6056fa-eb53-4b66-a50c-4d1be574d3cc
ORCID for Fernando Alvarez-Borges: ORCID iD orcid.org/0000-0002-6940-9918

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Date deposited: 09 Aug 2022 17:00
Last modified: 31 Jan 2023 03:06

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Contributors

Author: Fernando Alvarez-Borges ORCID iD
Author: Sharif Ahmed
Author: Robert C. Atwood

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