Concrete is a multi-phase and random heterogeneous material composed mainly of water, aggregate, and cement. The spatial distribution of these constituents strongly affects material performance. In addition, the voids present in cast concrete permit the passage of most air and water through the material, which significantly affects permeability and durability. Therefore, a proper investigation of the void distribution within concrete is important in evaluating its material characteristics. To visualize and investigate the spatial distribution of voids in a concrete specimen, X-ray CT images and probabilistic methods, including reconstruction, are used in this study. Two cement paste specimens with different void ratios are prepared, and a virtual specimen with a gradient distribution of voids through its thickness is reconstructed from the two real specimens. The characteristics of the void distribution for all three specimens are then examined using low-order probability functions and tortuosity. In addition, the permeability of each specimen is evaluated using finite element (FE) simulation, which is then compared with experimental data. From these results, we can confirm that the proposed reconstruction method can effectively generate a virtual cement paste specimen with a specific void distribution. Thus, the simulation tools adopted in this study can be utilized to supplement time-consuming experiments.
|Number of pages||9|
|Journal||Construction and Building Materials|
|Publication status||Published - 2015 Jul 15|
Bibliographical noteFunding Information:
This research was supported by a Korea Research Foundation Grant funded by the Korean Government ( KRF-2011-0029212 and KRF-2012R1A1A2006629 ). This work was also supported by the Industrial Strategic Technology Development Program (10041589) funded by the Ministry of Knowledge Economy (MKE, Korea). In addition, the authors would like to express our appreciation to Dr. Shinichiro Okazaki at Port and Airport Research Institute in Japan, who provided CT images of cement paste specimens and experimental data.
© 2015 Elsevier Ltd. All rights reserved.
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Building and Construction
- Materials Science(all)