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X-ray computed tomography images and network data of sands under compression

Ottawa sand and Angular sand consist of particles with distinct shapes. The x-ray computed tomography (XCT) image stacks of their in-situ confined compressive testings are provided in this paper. For each image stack, a contact network, a thermal network and a network feature - edge betweenness cent...

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Autores principales: Fei, Wenbin, Narsilio, Guillermo, van der Linden, Joost, Disfani, Mahdi, Miao, Xiuxiu, Yang, Baohua, Afshar, Tabassom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165412/
https://www.ncbi.nlm.nih.gov/pubmed/34095373
http://dx.doi.org/10.1016/j.dib.2021.107122
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author Fei, Wenbin
Narsilio, Guillermo
van der Linden, Joost
Disfani, Mahdi
Miao, Xiuxiu
Yang, Baohua
Afshar, Tabassom
author_facet Fei, Wenbin
Narsilio, Guillermo
van der Linden, Joost
Disfani, Mahdi
Miao, Xiuxiu
Yang, Baohua
Afshar, Tabassom
author_sort Fei, Wenbin
collection PubMed
description Ottawa sand and Angular sand consist of particles with distinct shapes. The x-ray computed tomography (XCT) image stacks of their in-situ confined compressive testings are provided in this paper. For each image stack, a contact network, a thermal network and a network feature - edge betweenness centrality - of each edge in the networks are also provided. The readers can use the image data to construct digital sands with applications of (1) extracting microstructural parameters such as particle size, particle shape, coordination number and more network features; (2) analysing mechanical behaviour and transport processes such as fluid flow, heat transfer and electrical conduction using either traditional simulation tools such as finite element method and discrete element method or newly network models which could be built based on the network files available here.
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spelling pubmed-81654122021-06-05 X-ray computed tomography images and network data of sands under compression Fei, Wenbin Narsilio, Guillermo van der Linden, Joost Disfani, Mahdi Miao, Xiuxiu Yang, Baohua Afshar, Tabassom Data Brief Data Article Ottawa sand and Angular sand consist of particles with distinct shapes. The x-ray computed tomography (XCT) image stacks of their in-situ confined compressive testings are provided in this paper. For each image stack, a contact network, a thermal network and a network feature - edge betweenness centrality - of each edge in the networks are also provided. The readers can use the image data to construct digital sands with applications of (1) extracting microstructural parameters such as particle size, particle shape, coordination number and more network features; (2) analysing mechanical behaviour and transport processes such as fluid flow, heat transfer and electrical conduction using either traditional simulation tools such as finite element method and discrete element method or newly network models which could be built based on the network files available here. Elsevier 2021-05-12 /pmc/articles/PMC8165412/ /pubmed/34095373 http://dx.doi.org/10.1016/j.dib.2021.107122 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Fei, Wenbin
Narsilio, Guillermo
van der Linden, Joost
Disfani, Mahdi
Miao, Xiuxiu
Yang, Baohua
Afshar, Tabassom
X-ray computed tomography images and network data of sands under compression
title X-ray computed tomography images and network data of sands under compression
title_full X-ray computed tomography images and network data of sands under compression
title_fullStr X-ray computed tomography images and network data of sands under compression
title_full_unstemmed X-ray computed tomography images and network data of sands under compression
title_short X-ray computed tomography images and network data of sands under compression
title_sort x-ray computed tomography images and network data of sands under compression
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165412/
https://www.ncbi.nlm.nih.gov/pubmed/34095373
http://dx.doi.org/10.1016/j.dib.2021.107122
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