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. 2016 May 19;9(5):388.
doi: 10.3390/ma9050388.

Evaluation of Microstructure and Transport Properties of Deteriorated Cementitious Materials from Their X-ray Computed Tomography (CT) Images

Michael Angelo B Promentilla  1 , Shermaine M Cortez  2 , Regina Anne Dc Papel  3 , Bernadette M Tablada  4 , Takafumi Sugiyama  5
Affiliations

Evaluation of Microstructure and Transport Properties of Deteriorated Cementitious Materials from Their X-ray Computed Tomography (CT) Images

Michael Angelo B Promentilla et al. Materials (Basel). .

Abstract

Pore structure, tortuosity and permeability are considered key properties of porous materials such as cement pastes to understand their long-term durability performance. Three-dimensional image analysis techniques were used in this study to quantify pore size, effective porosity, tortuosity, and permeability from the X-ray computed tomography (CT) images of deteriorated pastes that were subjected to accelerated leaching test. X-ray microtomography is a noninvasive three-dimensional (3D) imaging technique which has been recently gaining attention for material characterization. Coupled with 3D image analysis, the digitized pore can be extracted and computational simulation can be applied to the pore network to measure relevant microstructure and transport properties. At a spatial resolution of 0.50 μm, the effective porosity (ψe) was found to be in the range of 0.04 to 0.33. The characteristic pore size (d) using a local thickness algorithm was found to be in the range of 3 to 7 μm. The geometric tortuosity (τg) based on a 3D random walk simulation in the percolating pore space was found to be in the range of 2.00 to 7.45. The water permeability values (K) using US NIST Permeability Stokes Solver range from an order of magnitudes of 10-14 to 10-17 m². Indications suggest that as effective porosity increases, the geometric tortuosity increases and the permeability decreases. Correlation among these microstructure and transport parameters is also presented in this study.

Keywords: 3D image analysis; X-ray microtomography; accelerated leaching; deteriorated cement paste; porosity; tortuosity; water permeability.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Schematic diagram of the accelerated leaching test of cement paste and regions of interest where 5 specimens were obtained (OPC_de1, OPC_de2, OPC_de3, OPC_de4, and OPC_de5).
Figure 2
Figure 2
Extraction and visualization of pore space from CT images of deteriorated cement pastes: (a) An 8-bit representative slice (2000 × 2000 voxels) obtained from OPC-de2; (b) The volume of interest (3003 voxels) obtained from the normalized data set; (c) The resulting 3D stack after denoising; (d) A 3D visualization of the segmented total porosity of the VOI; (e) A 3D visualization of the largest percolating pore cluster in the VOI or the effective porosity of the VOI.
Figure 3
Figure 3
Image analysis for quantification of porosity and pore size: (a) An 8-bit representative grayscale slice (300 × 300 voxels) from VOI; (b) The binary image after segmentation (segmented porosity is imaged as black voxels); (c) The binary image after multiple cluster labeling (largest percolating pore cluster or effective porosity is imaged as black voxels whereas the smaller or isolated pore clusters are imaged as gray voxels); (d) Image resulting from local thickness algorithm to determine the mean pore size.
Figure 4
Figure 4
Sample output from the 3D Random Walk Simulation: (a) 3D trajectory of a walker in free space; (b) 3D trajectory of a walker in closed and isolated spherical pore; (c) plot of mean square displacement (<r>2) vs. lattice walk time; (d) plot of the normalized self-diffusion coefficient (D(t)) vs. lattice walk time.
Figure 5
Figure 5
Sample trajectory of a walker in a digitized pore network of deteriorated cement paste including the projected trajectory in three orthogonal planes.
Figure 5
Figure 5
Sample trajectory of a walker in a digitized pore network of deteriorated cement paste including the projected trajectory in three orthogonal planes.
Figure 6
Figure 6
Sample model pore structure used to validate the Stokes permeability solver.
Figure 7
Figure 7
Summary of microstructure and transport properties in different regions: (a) Segmented total porosity; (b) effective porosity; (c) mean pore size (m); (d) tortuosity; (e) intrinsic permeability (m2); (f) Non-dimensional permeability, i.e., intrinsic permeability normalized by square of the mean pore size.
Figure 8
Figure 8
Scatter plot between effective porosity and tortuosity.
Figure 9
Figure 9
Scatter plot between effective porosity and intrinsic permeability (m2).
Figure 10
Figure 10
Scatter plot between tortuosity and intrinsic permeability (m2).
Figure 11
Figure 11
A non-dimensional model for microstructure-transport property correlation.
See this image and copyright information in PMC

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