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16 pages, 2910 KiB

Open AccessFeature PaperArticle

In-Situ X-ray Imaging Of Sublimating Spin-Frozen Solutions

by Wannes Goethals, Brecht Vanbillemont, Joris Lammens, Thomas De Beer, Chris Vervaet and Matthieu N. Boone

Materials 2020, 13(13), 2953; https://0-doi-org.brum.beds.ac.uk/10.3390/ma13132953 - 1 Jul 2020

Cited by 3 | Viewed by 2815

Abstract

Spin-freeze-drying is a promising technique to enable long-term storage of pharmaceutical unit doses of aqueous drug solutions. To investigate the sublimation of the ice during the primary phase of freeze-drying, X-ray imaging can yield crucial temporally resolved information on the local dynamics. In [...] Read more.

Spin-freeze-drying is a promising technique to enable long-term storage of pharmaceutical unit doses of aqueous drug solutions. To investigate the sublimation of the ice during the primary phase of freeze-drying, X-ray imaging can yield crucial temporally resolved information on the local dynamics. In this paper, we describe a methodology to investigate the sublimation front during single unit-dose freeze-drying using 4D in-situ X-ray imaging. Three spin-frozen samples of different solutions were imaged using this methodology and the process characteristics were analysed and reduced to two-dimensional feature maps. Full article

(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)

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21 pages, 17821 KiB

Open AccessArticle

Equivalent Pore Channel Model for Fluid Flow in Rock Based on Microscale X-ray CT Imaging

by Chae-Soon Choi, Yong-Ki Lee and Jae-Joon Song

Materials 2020, 13(11), 2619; https://0-doi-org.brum.beds.ac.uk/10.3390/ma13112619 - 8 Jun 2020

Cited by 14 | Viewed by 2975

Abstract

Pore-scale modeling with a reconstructed rock microstructure has become a dominant technique for fluid flow characterization in rock thanks to technological improvements in X-ray computed tomography (CT) imaging. A new method for the construction of a pore channel model from micro-CT image analysis [...] Read more.

Pore-scale modeling with a reconstructed rock microstructure has become a dominant technique for fluid flow characterization in rock thanks to technological improvements in X-ray computed tomography (CT) imaging. A new method for the construction of a pore channel model from micro-CT image analysis is suggested to improve computational efficiency by simplifying a highly complex pore structure. Ternary segmentation was applied through matching a pore volume experimentally measured by mercury intrusion porosimetry with a CT image voxel volume to distinguish regions denoted as “apparent” and “indistinct” pores. The developed pore channel model, with distinct domains of different pore phases, captures the pore shape dependence of flow in two dimensions and a tortuous flow path in three dimensions. All factors determining these geometric characteristics were identified by CT image analysis. Computation of an interaction flow regime with apparent and indistinct pore domains was conducted using both the Stokes and Brinkman equations. The coupling was successfully simulated and evaluated against the experimental results of permeability derived from Darcy’s law. Reasonable agreement was found between the permeability derived from the pore channel model and that estimated experimentally. However, the model is still incapable of accurate flow modeling in very low-permeability rock. Direct numerical simulation in a computational domain with a complex pore space was also performed to compare its accuracy and efficiency with the pore channel model. Both schemes achieved reasonable results, but the pore channel model was more computationally efficient. Full article

(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)

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17 pages, 4088 KiB

Open AccessArticle

In-situ X-ray Differential Micro-tomography for Investigation of Water-weakening in Quasi-brittle Materials Subjected to Four-point Bending

by Petr Koudelka, Tomas Fila, Vaclav Rada, Petr Zlamal, Jan Sleichrt, Michal Vopalensky, Ivana Kumpova, Pavel Benes, Daniel Vavrik, Leona Vavro, Martin Vavro, Milos Drdacky and Daniel Kytyr

Materials 2020, 13(6), 1405; https://0-doi-org.brum.beds.ac.uk/10.3390/ma13061405 - 20 Mar 2020

Cited by 11 | Viewed by 3348

Abstract

Several methods, including X-ray radiography, have been developed for the investigation of the characteristics of water-saturated quasi-brittle materials. Here, the water content is one of the most important factors influencing their strength and fracture properties, in particular, as regards to porous building materials. [...] Read more.

Several methods, including X-ray radiography, have been developed for the investigation of the characteristics of water-saturated quasi-brittle materials. Here, the water content is one of the most important factors influencing their strength and fracture properties, in particular, as regards to porous building materials. However, the research concentrated on the three-dimensional fracture propagation characteristics is still significantly limited due to the problems encountered with the instrumentation requirements and the size effect. In this paper, we study the influence of the water content in a natural quasi-brittle material on its mechanical characteristics and fracture development during in-situ four-point bending by employing high-resolution X-ray differential micro-tomography. The cylindrical samples with a chevron notch were loaded using an in-house designed four-point bending loading device with the vertical orientation of the sample. The in-house designed modular micro-CT scanner was used for the visualisation of the specimen’s behaviour during the loading experiments. Several tomographic scans were performed throughout the force-displacement diagrams of the samples. The reconstructed 3D images were processed using an in-house developed differential tomography and digital volume correlation algorithms. The apparent reduction in the ultimate strength was observed due to the moisture content. The crack growth process in the water-saturated specimens was identified to be different in comparison with the dry specimens. Full article

(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)

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33 pages, 8943 KiB

Open AccessArticle

Computed Tomography 3D Super-Resolution with Generative Adversarial Neural Networks: Implications on Unsaturated and Two-Phase Fluid Flow

by Nick Janssens, Marijke Huysmans and Rudy Swennen

Materials 2020, 13(6), 1397; https://0-doi-org.brum.beds.ac.uk/10.3390/ma13061397 - 19 Mar 2020

Cited by 31 | Viewed by 4589

Abstract

Fluid flow characteristics are important to assess reservoir performance. Unfortunately, laboratory techniques are inadequate to know these characteristics, which is why numerical methods were developed. Such methods often use computed tomography (CT) scans as input but this technique is plagued by a resolution [...] Read more.

Fluid flow characteristics are important to assess reservoir performance. Unfortunately, laboratory techniques are inadequate to know these characteristics, which is why numerical methods were developed. Such methods often use computed tomography (CT) scans as input but this technique is plagued by a resolution versus sample size trade-off. Therefore, a super-resolution method using generative adversarial neural networks (GANs) was used to artificially improve the resolution. Firstly, the influence of resolution on pore network properties and single-phase, unsaturated, and two-phase flow was analysed to verify that pores and pore throats become larger on average and surface area decreases with worsening resolution. These observations are reflected in increasingly overestimated single-phase permeability, less moisture uptake at lower capillary pressures, and high residual oil fraction after waterflooding. Therefore, the super-resolution GANs were developed which take low (12 µm) resolution input and increase the resolution to 4 µm, which is compared to the expected high-resolution output. These results better predicted pore network properties and fluid flow properties despite the overestimation of porosity. Relevant small pores and pore surfaces are better resolved thus providing better estimates of unsaturated and two-phase flow which can be heavily influenced by flow along pore boundaries and through smaller pores. This study presents the second case in which GANs were applied to a super-resolution problem on geological materials, but it is the first one to apply it directly on raw CT images and to determine the actual impact of a super-resolution method on fluid predictions. Full article

(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)

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16 pages, 4098 KiB

Open AccessArticle

Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites

by Yuriy Sinchuk, Pierre Kibleur, Jan Aelterman, Matthieu N. Boone and Wim Van Paepegem

Materials 2020, 13(4), 936; https://0-doi-org.brum.beds.ac.uk/10.3390/ma13040936 - 20 Feb 2020

Cited by 44 | Viewed by 3904 | Correction

Abstract

The purpose of this work is to find an effective image segmentation method for lab-based micro-tomography (µ-CT) data of carbon fiber reinforced polymers (CFRP) with insufficient contrast-to-noise ratio. The segmentation is the first step in creating a realistic geometry (based on µ-CT) for [...] Read more.

The purpose of this work is to find an effective image segmentation method for lab-based micro-tomography (µ-CT) data of carbon fiber reinforced polymers (CFRP) with insufficient contrast-to-noise ratio. The segmentation is the first step in creating a realistic geometry (based on µ-CT) for finite element modelling of textile composites on meso-scale. Noise in X-ray imaging data of carbon/polymer composites forms a challenge for this segmentation due to the very low X-ray contrast between fiber and polymer and unclear fiber gradients. To the best of our knowledge, segmentation of µ-CT images of carbon/polymer textile composites with low resolution data (voxel size close to the fiber diameter) remains poorly documented. In this paper, we propose and evaluate different approaches for solving the segmentation problem: variational on the one hand and deep-learning-based on the other. In the author’s view, both strategies present a novel and reliable ground for the segmentation of µ-CT data of CFRP woven composites. The predictions of both approaches were evaluated against a manual segmentation of the volume, constituting our “ground truth”, which provides quantitative data on the segmentation accuracy. The highest segmentation accuracy (about 4.7% in terms of voxel-wise Dice similarity) was achieved using the deep learning approach with U-Net neural network. Full article

(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)

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21 pages, 5808 KiB

Open AccessArticle

Quantification of Uncertainty and Best Practice in Computing Interfacial Curvature from Complex Pore Space Images

by Takashi Akai, Qingyang Lin, Abdulla Alhosani, Branko Bijeljic and Martin J. Blunt

Materials 2019, 12(13), 2138; https://0-doi-org.brum.beds.ac.uk/10.3390/ma12132138 - 3 Jul 2019

Cited by 25 | Viewed by 3505

Abstract

Recent advances in high-resolution three-dimensional X-ray CT imaging have made it possible to visualize fluid configurations during multiphase displacement at the pore-scale. However, there is an inherited difficulty in image-based curvature measurements: the use of voxelized image data may introduce significant error, which [...] Read more.

Recent advances in high-resolution three-dimensional X-ray CT imaging have made it possible to visualize fluid configurations during multiphase displacement at the pore-scale. However, there is an inherited difficulty in image-based curvature measurements: the use of voxelized image data may introduce significant error, which has not—to date—been quantified. To find the best method to compute curvature from micro-CT images and quantify the likely error, we performed drainage and imbibition direct numerical simulations for an oil/water system on a bead pack and a Bentheimer sandstone. From the simulations, local fluid configurations and fluid pressures were obtained. We then investigated methods to compute curvature on the oil/water interface. The interface was defined in two ways; in one case the simulated interface with a sub-resolution smoothness was used, while the other was a smoothed interface extracted from synthetic segmented data based on the simulated phase distribution. The curvature computed on these surfaces was compared with that obtained from the simulated capillary pressure, which does not depend on the explicit consideration of the shape of the interface. As distinguished from previous studies which compared an average or peak curvature with the value derived from the measured macroscopic capillary pressure, our approach can also be used to study the pore-by-pore variation. This paper suggests the best method to compute curvature on images with a quantification of likely errors: local capillary pressures for each pore can be estimated to within 30% if the average radius of curvature is more than 6 times the image resolution, while the average capillary pressure can also be estimated to within 11% if the average radius of curvature is more than 10 times the image resolution. Full article

(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)

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13 pages, 5005 KiB

Open AccessArticle

X-ray Computed Tomography for Characterization of Expanded Polystyrene (EPS) Foam

by Redouane Meftah, Jeroen Van Stappen, Sylvain Berger, Gary Jacqus, Jean-Yves Laluet, Paul-Henri Guering, Luc Van Hoorebeke and Veerle Cnudde

Materials 2019, 12(12), 1944; https://0-doi-org.brum.beds.ac.uk/10.3390/ma12121944 - 17 Jun 2019

Cited by 11 | Viewed by 3809

Abstract

Expanded polystyrene (EPS) foam is widely used in building and construction applications for thermal and acoustic insulation. This material is nearly transparent for X-rays, making it difficult to characterize its pore structure in 3D with X-ray tomography. Because of this difficulty, the pore [...] Read more.

Expanded polystyrene (EPS) foam is widely used in building and construction applications for thermal and acoustic insulation. This material is nearly transparent for X-rays, making it difficult to characterize its pore structure in 3D with X-ray tomography. Because of this difficulty, the pore network is often not investigated and is, thus, poorly known. Since this network controls different physical properties, such as the sound absorption, it is crucial to understand its overall structure. In this manuscript, we show how to reveal the pore network of EPS foams through the combination of high resolution X-ray tomography (micro-CT) and saturation techniques. The foams were saturated with CsCl-brine, which acts as a contrasting agent in X-ray micro-CT imaging. This allowed us to separate the beads, making up the foam, from the pore network. Based on the 3D micro-CT results, we were able to assess a representative elementary volume for the polystyrene, which allows for calculating the acoustical parameters from the Johnson–Champoux–Allard (JCA) model, the pore and bead size distribution. The 3D data was also used as input to simulate sound absorption curves. The parametric study showed that an increase in the bead size influenced the sound absorption of the material. We showed that, by doubling the diameter of beads, the absorption coefficient was doubled in certain ranges of frequency. Full article

(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)

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2 pages, 162 KiB

Open AccessCorrection

Correction: Sinchuk et al. Variational and Deep Learning Segmentation of Very-Low-Contrast X-ray Computed Tomography Images of Carbon/Epoxy Woven Composites. Materials 2020, 13, 936

by Yuriy Sinchuk, Pierre Kibleur, Jan Aelterman, Matthieu N. Boone and Wim Van Paepegem

Materials 2022, 15(22), 8168; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15228168 - 17 Nov 2022

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Abstract

We would like to change the authors’ affiliation on the recent published paper [...] Full article

(This article belongs to the Special Issue Novel Acquisition and Analysis Methods for X-ray Micro-CT in Materials Sciences)

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