Quantification of fabric in cemented granular materials

Singh, Saurabh; Miers, John C.; Saldaña, Christopher; Murthy, Tejas G.

doi:10.1016/j.compgeo.2020.103644

Cited by 7 publications

(4 citation statements)

References 48 publications

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“…The distribution of volume of particles is similar but there is a small difference in the actual counts. Both methods predict that most contacts are oriented along the z-direction (direction of gravity); this observation is consistent with previous studies on fabric of granular materials and cemented granular materials [31,44]. The differences in counts of histograms is due to oversegmentation of the particles by the watershed-based method (discussed in section 6.4).…”

Section: Benchmarking and Experimental Resultssupporting

confidence: 89%

“…We compute and visualize the segmentation and connectivity network for the packing and highlight observed statistical trends. Finally, we compare the quality of computed results and ease of computation with a recent watershed-based pipeline for the analysis of cemented granular materials [44]. All computational experiments were performed on a workstation with an Intel Xeon E5-1660 v4 @ 3.8 GHz processor with 8 cores, 128 GB main memory, and an Nvidia Quadro P2000 graphics card with 6 GB RAM.…”

Section: Benchmarking and Experimental Resultsmentioning

confidence: 99%

“…We analyze a 3D CT scan of a packing of sand particles 515 coated with epoxy at the contacts. The packing has 516 a contact bound structure i.e., the cementation exists 517 only at the contacts in a skeleton of sand particles [44]. 518 The scan has a dimension of 888 × 912 × 1360 voxels 519 with a resolution of 12.5 µm per voxel.…”

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confidence: 99%

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Morse theory-based segmentation and fabric quantification of granular materials

et al. 2021

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This article presents a robust Morse theory-1 based framework for segmenting 3D x-ray computed 2 tomography image (CT) and computing the fabric, rel-3 ative arrangement of particles, of granular ensembles. 4 The framework includes an algorithm for computing the 5 segmentation, a data structure for storing the segmenta-6 tion and representing both individual particles and the 7 connectivity network, and visualizations of topological 8 descriptors of the CT image that enable interactive ex-9 ploration. The Morse theory-based framework produces 10 superior quality segmentation of a granular ensemble as 11 compared to prior approaches based on the watershed 12 transform. The accuracy of the connectivity network 13 also improves. Further, the framework supports the effi-14 cient computation of various distribution statistics on 15 the segmentation and the connectivity network. Such 16 a comprehensive characterization and quantification of 17 the fabric of granular ensembles is the first step towards 18 a multiple length scale understanding of the behavior. 19 Keywords Granular ensemble • fabric • segmentation • 20 particle connectivity network • Morse theory • 21 Morse-Smale complex • topological persistence.

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Section: Benchmarking and Experimental Resultssupporting

confidence: 89%

Section: Benchmarking and Experimental Resultsmentioning

confidence: 99%

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Morse theory-based segmentation and fabric quantification of granular materials

et al. 2021

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“…An example is the use of X-CT to quantify fabric in a polymer-bonded frictional granular material. Analyzing its constituents' relative orientation, described by fabric tensors, allows for a systematical structure characterization [SJCT20]. Such knowledge can then be exploited in numerical simulations, e.g., to assess the stability of dams [RBM20] or waste reservoirs [MGV*17, RBR*20].…”

Section: Geomechanicsmentioning

confidence: 99%

Visualization of Tensor Fields in Mechanics

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Kretzschmar

et al. 2021

Computer Graphics Forum

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Tensors are used to describe complex physical processes in many applications. Examples include the distribution of stresses in technical materials, acting forces during seismic events, or remodeling of biological tissues. While tensors encode such complex information mathematically precisely, the semantic interpretation of a tensor is challenging. Visualization can be beneficial here and is frequently used by domain experts. Typical strategies include the use of glyphs, color plots, lines, and isosurfaces. However, data complexity is nowadays accompanied by the sheer amount of data produced by large-scale simulations and adds another level of obstruction between user and data. Given the limitations of traditional methods, and the extra cognitive effort of simple methods, more advanced tensor field visualization approaches have been the focus of this work. This survey aims to provide an overview of recent research results with a strong application-oriented focus, targeting applications based on continuum mechanics, namely the fields of structural, bio-, and geomechanics. As such, the survey is complementing and extending previously published surveys. Its utility is twofold: (i) It serves as basis for the visualization community to get an overview of recent visualization techniques. (ii) It emphasizes and explains the necessity for further research for visualizations in this context.

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