TY - JOUR
T1 - Evaluation of the anisotropy of the void distribution and the stiffness of lightweight aggregates using CT imaging
AU - Chung, Sang Yeop
AU - Han, Tong Seok
AU - Yun, Tae Sup
AU - Youm, Kwang Soo
PY - 2013
Y1 - 2013
N2 - The void distribution in concrete materials strongly affects its material properties. Therefore, identification of the spatial void distribution is important to understand and estimate material behavior. To quantify the void distribution inside lightweight aggregates, a computed tomography (CT) image can be effective, as it is non-destructive. Here, three-dimensional void images of lightweight aggregates are generated by stacking cross-sectional CT images. The spatial distribution of voids in the aggregate along a direction is visualized on a sphere using a probability distribution function. To describe the void distribution of aggregates, a two-point correlation function is used. The stiffness of the lightweight aggregate for a direction is also examined. We find that the direction-based probability distribution and stiffness from the CT images are effective for characterizing the void distributions of aggregates. In addition, the anisotropy ratio of voids and the stiffness are closely related along with the void volume fraction.
AB - The void distribution in concrete materials strongly affects its material properties. Therefore, identification of the spatial void distribution is important to understand and estimate material behavior. To quantify the void distribution inside lightweight aggregates, a computed tomography (CT) image can be effective, as it is non-destructive. Here, three-dimensional void images of lightweight aggregates are generated by stacking cross-sectional CT images. The spatial distribution of voids in the aggregate along a direction is visualized on a sphere using a probability distribution function. To describe the void distribution of aggregates, a two-point correlation function is used. The stiffness of the lightweight aggregate for a direction is also examined. We find that the direction-based probability distribution and stiffness from the CT images are effective for characterizing the void distributions of aggregates. In addition, the anisotropy ratio of voids and the stiffness are closely related along with the void volume fraction.
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U2 - 10.1016/j.conbuildmat.2013.07.082
DO - 10.1016/j.conbuildmat.2013.07.082
M3 - Article
AN - SCOPUS:84883123964
SN - 0950-0618
VL - 48
SP - 998
EP - 1008
JO - Construction and Building Materials
JF - Construction and Building Materials
ER -