Correlation between low-order probability distribution functions and percolation of porous concrete

Abstract

Concrete is a multi-phase material whose material properties are strongly affected by phase distribution. It is important to identify the spatial distribution of voids in concrete because voids have a significant effect on mechanical behaviour and percolation. Therefore, a proper method to describe the void distribution of the material is needed. This paper describes how computed tomography (CT) was used to examine and quantify the void distribution of porous concrete specimens. Virtual three-dimensional porous concrete specimens were created using CT. Then, low-order probability distribution functions such as two-point correlation, lineal-path and two-point cluster functions were used to characterise the void distribution. Based on CT image analysis, the correlation of hydraulic conductivity between experiment results and probability distribution functions of porous concrete is examined. It is confirmed that low-order probability functions and percolation of porous concrete are correlated and that the low-order probability functions are efficient and effective in describing percolation within porous concrete.