Studying structure and determining permeability of materials based on X-Ray microtomography data (using porous ceramics as an example)

Gerke, Kirill M.; Корост, Д. В.; Vasilyev, Roman; Karsanina, Marina V.; Тарасовский, В. П.

doi:10.1134/s002016851509006x

Cited by 15 publications

(6 citation statements)

References 13 publications

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“…Figure 6also shows the similarity between two velocity fields computed using FDMSS for an original 3D image of ceramics (Gerke et al, 2015b) and for its subsequent stochastic reconstruction (Gerke and Karsanina, 2015). The resulting permeabilities differ by around 10%, consistent with a more realistic representation of connected pore spaces when using the modified Yeong-Torquato approach.In addition to pore network reconstructions, one can also generate pore geometries with predetermined pore sizes and permeabilities(Karsanina et al, 2015b) using analytically constructed M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 20 correlation functions…”

mentioning

confidence: 99%

Finite-difference method Stokes solver (FDMSS) for 3D pore geometries: Software development, validation and case studies

Gerke

Vasilyev

Khirevich

et al. 2018

Computers & Geosciences

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Permeability is one of the fundamental properties of porous media and is required for largescale Darcian fluid flow and mass transport models. Whilst permeability can be measured directly at a range of scales, there are increasing opportunities to evaluate permeability from pore-scale fluid flow simulations. We introduce the free software Finite-Difference Method Stokes Solver (FDMSS) that solves Stokes equation using a finite-difference method (FDM) directly on voxelized 3D pore geometries (i.e. without meshing). Based on explicit convergence studies, validation on sphere packings with analytically known permeabilities, and comparison against lattice-Boltzmann and

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mentioning

confidence: 99%

Finite-difference method Stokes solver (FDMSS) for 3D pore geometries: Software development, validation and case studies

Gerke

Vasilyev

Khirevich

et al. 2018

Computers & Geosciences

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“…The sample after the test is suitable for further use because the method is not invasive and does not damage the material during testing, unlike the mercury porosity method in which the mercury remains in the sample, and a high mercury pressure may entail sample distortion. Previous methods aimed at characterizing the internal structure of porous materials with the use of microtomography were related to specific materials [17][18][19][20][21] and their applications [22] (the studies used microtomography to characterize porosity in terms of material permeability). The analysis proposed in the above articles is similar to the developed method in this study.…”

Section: Resultsmentioning

confidence: 99%

“…Previous methods aimed at characterizing the internal structure of porous materials with the use of microtomography were related to specific materials [ 17 , 18 , 19 , 20 , 21 ] and their applications [ 22 ] (the studies used microtomography to characterize porosity in terms of material permeability). The analysis proposed in the above articles is similar to the developed method in this study.…”

Section: Resultsmentioning

confidence: 99%

“…Despite technological advances, 3D imaging techniques such as X-ray microtomography are often used only for qualitative evaluation of materials through their visualization. Methods for quantifying the internal structure of porous materials are still few and related to specific materials and their applications [ 17 , 18 , 19 , 20 , 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

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Ceramic Biomaterial Pores Stereology Analysis by the Use of Microtomography

et al. 2021

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The main aim of this study was to analyze microtomographic data to determine the geometric dimensions of a ceramic porous material’s internal structure. Samples of a porous corundum biomaterial were the research material. The samples were prepared by chemical foaming and were measured using an X-ray scanner. In the next stage, 3D images of the samples were generated and analyzed using Thermo Scientific Avizo software. The analysis enabled the isolation of individual pores. Then, the parameters characterizing the pore geometry and the porosity of the samples were calculated. The last part of the research consisted of verifying the developed method by comparing the obtained results with the parameters obtained from the microscopic examinations of the biomaterial. The comparison of the results confirmed the correctness of the developed method. The developed methodology can be used to analyze biomaterial samples to assess the geometric dimensions of biomaterial pores.

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“…To verify the newly proposed modified phase-retrieval algorithm and compare it against classical technique, we chose three 3D porous media images of different genesis: artificial ceramic [41], sandstone and carbonate rocks [42]. The choice was motivated by a wide range of porosities within these samples and their relative homogeneity and isotropy.…”

Section: F Samples For Reconstruction and Comparison Between Techniquesmentioning

confidence: 99%

Adaptive phase-retrieval stochastic reconstruction with correlation functions: 3D images from 2D cuts

Cherkasov,

Ananev,

Karsanina

et al. 2021

Preprint

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Precise characterization of three-dimensional heterogeneous media is indispensable in finding the relationships between structure and macroscopic physical properties (permeability, conductivity, and others). The most widely used experimental methods (electronic and optical microscopy) provide high-resolution bi-dimensional images of the samples of interest. However, 3D material inner microstructure registration is needed to apply numerous modeling tools. Numerous research areas search for cheap and robust methods to obtain "full" 3D information about the structure of the studied sample from its 2D cuts. In this work, we develop a dynamic phase-retrieval stochastic reconstruction algorithm that can create 3D replicas from 2D original images -DDTF. The DDTF is free of artifacts characteristic of previously proposed phase-retrieval techniques. While based on a two-point S2 correlation function, any correlation function or other morphological metrics can be accounted for during the reconstruction, thus, paving the way to the hybridization of different reconstruction techniques. In this work, we use two-point probability and surface-surface functions for optimization. To test DDTF, we performed reconstructions for three binary porous media samples of different genesis: sandstone, carbonate, and ceramic. Based on computed permeability and connectivity (C2 and L2 correlation functions), we have shown that the proposed technique in terms of accuracy is comparable to the classic simulated annealing-based reconstruction method but is computationally very effective. Our findings open the possibility of utilizing DDTF to produce fast or crude replicas further polished by other reconstruction techniques such as simulated annealing or process-based methods. Improving the quality of reconstructions based on phase-retrieval by adding additional metrics into the reconstruction procedure is possible for future work.

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Studying structure and determining permeability of materials based on X-Ray microtomography data (using porous ceramics as an example)

Cited by 15 publications

References 13 publications

Finite-difference method Stokes solver (FDMSS) for 3D pore geometries: Software development, validation and case studies

Finite-difference method Stokes solver (FDMSS) for 3D pore geometries: Software development, validation and case studies

Ceramic Biomaterial Pores Stereology Analysis by the Use of Microtomography

Adaptive phase-retrieval stochastic reconstruction with correlation functions: 3D images from 2D cuts

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