• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2A
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• pp.121-127
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• 2011

Spatial distribution of void space in concrete materials strongly affects mechanical and physical behaviors. Therefore, the identification of characteristic void distribution helps understand material properties and is essential to estimate the integrity of material performance. The 3D micro CT (X-ray microtomography) is implemented to examine and to quantify the void distribution of a lightweight aggregate concrete using an image analysis technique and probabilistic approach in this study. The binarization and subsequent stacking of 2D cross-sectional images virtually create 3D images of targeting void space. Then, probability distribution functions such as two-point correlation and lineal-path functions are applied for void characterization. The lightweight aggregates embedded within the concrete are individually analyzed to construct the intra-void space. Results shows that the low-order probability functions and the density distribution based on the 3D micro CT images are applicable and useful methodology to characterize spatial distribution of void space and constituents in concrete.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.3
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• pp.227-235
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• 2012

The void distribution in concrete materials strongly affects its material properties. Therefore, the identification of spatial distribution of void is important to understand and estimate material behavior. To examine and quantify the void distribution inside lightweight aggregates, CT(computed tomography) image is used. 3D lightweight aggregate images are generated by stacking of cross-sectional images from CT. Spatial distribution of void of aggregate along the direction is visualized on the sphere using probability distribution function. Stiffness of lightweight aggregate for the directions is also examined. It is confirmed that direction-based probability distribution and stiffness from CT images are effective in characterizing void distributions of aggregates.

• The Journal of Engineering Geology
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• v.24 no.3
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• pp.353-362
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• 2014

Pore structures in porous rock play an important role in hydraulic & mechanical behaviour of rock. Porosity, size distribution and orientation of pores represent the characteristics of pore structures of porous rock. While effective porosity can be measured easily by conventional experiment, pore size distribution is hard to be quantified due to the lack of corresponding experiment. We assessed pore size distribution of Berea sandstone using X-ray CT image based analysis combined with associated images processing, i.e., image filtering, binarization and skeletonization subsequently followed by the assessment of local thickness and star chord length. The aim of this study is to propose a new and effective way to evaluate pore structures of porous rock using X-ray CT based analysis for pore size distribution.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1A
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• pp.31-37
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• 2012

The phase distribution in concrete materials strongly affects its material properties. It is important to identify the spatial distribution of void in concrete because the void in concrete materials affects mechanical behavior and permeability significantly. Therefore, a proper method to describe the void distribution of a material is needed. In this research, CT(computed tomography) is used to examine and to quantify the void distribution of porous concrete specimens. 3D concrete digital specimens are created by subsequent stacking of 2D cross-sectional images from CT. Then, probability distribution functions such as two-point correlation, lineal-path and two-point cluster functions are used for void distribution characterization. It is confirmed that probability distribution functions obtained from CT images are effective in characterizing void distributions including the anisotropy and percolation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.5
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• pp.463-469
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• 2016

In this study, a virtual specimen with a linear continuous gradient of void ratio (FGM: Functional Graded Material) is constructed using low-order probability functions of two real cement paste specimens. Two real specimens with difference void ratios are taken from X-ray CT to construct the virtual specimen. A virtual specimen with a gradient void distribution, whose average void ratio is between void ratios of two homogeneous real specimens, is constructed using a stochastic optimization approach. The void ratio distribution is assumed to be linear, and continuously varies in the vertical direction. In this study, a gradient term of void ratio is incorporated into the objective function as well as low-order probability functions from the previous research. To confirm the effect of gradient void distribution on the material response, air permeability is evaluated using finite element analysis. The analysis results are compared with experimental results, and confirm the effect of gradient void distribution on permeability.

• Geotechnical Engineering
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• v.4 no.3
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• pp.5-18
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• 1988

This study aims at scrutinizing the relationships among the frequency distribution of voids the relative density and the shear strength for the three types of different granular materials. The main results summarized are as follows: (1) The frequency distribution of void ratio of glass beads can be approximated by the negative exponential distribution proposed by Shahinpoor (1981), while as the particle shape changes from spherical to angular the frequency of the denser voids decreases and the distributions are well presented by the beta distribution. (2) For all materials, the standard deviation of void ratio increases with decreasing both the relative density of the material and sphericity of particle. (3) It was found that shear strength of the material was a function of not only the mean void ratio and its standard deviation, but also of the shape of the probability density function of the distribution of void ratio. The more the frequency distribution of void inclines towards the denser voids, the higher the shear strength of the material and vice versa.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6A
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• pp.449-456
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• 2011

Spacing factor proposed by Power is a concept of averaging air void spacing composed of geometric models. Thus, there's a limitation on simulating actual air void characteristics in concrete. This study presents SDI(spacing distribution index) to overcome the limitation of spacing factor. SDI is also evaluated through comparing SDI with SF(spacing factor). In this study, it was confirmed that SF decreased due to increasing air-entrainer content but SDI increased. This occurs because SDI is the area of spacing distribution curve and SDI increases with increasing the frequency of spacing. SDI is evaluated to have better coverage below $300{\mu}m$ of SF so that determination of critical point of SDI above 80% of durability index can be easily obtained with more reliability. SDI is the area of spacing distribution curve and reflects actual air void characteristics in concrete. A comparative study of SDI and results of freeze-thaw test will be performed later.

• Korean Journal of Soil Science and Fertilizer
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• v.26 no.4
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• pp.284-288
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• 1993

Tow Kinds of Soils, vertisol and alfisol, were selected and analyzed pore space distribution(PSD) by mercury intrusion method and soil water potential after freeze-drying from different water conditions, such as 0.033MPa, 1.5MPa and ovendry. The PSD values measured by mercury intrusion method were higher in large pores than the values from soil water potential. Also, there were big differences of PSD by the changes of the water content befor freeze-drying.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.27-34
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• 2022

Since water flow in the ground depends on the pore structure composed of soil grains, equations to predict the hydraulic properties based on the grain size have low accuracy. This paper presents a methodology to compute constriction-pore size distribution by Silveria's method and estimate saturated and unsaturated hydraulic properties of soils. Well-graded soil shows a uni-modal pore size distribution, and poor-graded soil does a bimodal distribution. Among theoretical models for saturated hydraulic conductivity using pore size distribution, Marshall model is well-matched with experimental results. Model formulas for soil-water characteristic curves and unsaturated hydraulic conductivity using the pore size distribution are proposed for hydraulic analysis of unsaturated soil. Continuous research is needed to select a model suitable to estimate hydraulic properties by applying the developed model formulas to various soils.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.4
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• pp.407-414
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• 2010

Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.