Simplified approach for quantitative analysis of hardened concrete microstructure using autocorrelation function

Abstract

In this paper, the internal microstructures of three different concrete mixtures were investigated through digital
image analysis procedure conducted on a set of 60 cross-sectional images of hardened concrete specimens.
To quantitatively describe the geometry and spatial organization of all the components within the hardened concretes and measure the heterogeneity of different concrete mixtures and sample shapes, a two-dimensional
Autocorrelation Function (ACF) analysis program was performed on a series of 60 scanned images of internal
cross-sectional images. This enabled us to define a correlation range called the microstructural characteristic
length, l_i, which can be used as: (i) an indicator to quantify the properties on the domain size of the internal microstructure of hardened concrete, and (ii) an input parameter for constitutive modeling or for estimating the
Representative Volume Element (RVE) of concrete. As the image analysis procedure based on ACF does not
require the segmentation of the images, the method proposed in the present paper provides a simple and useful way of quantifying the microstructure of concrete for many practical purposes.