The effect of random porosity field on supercritical carbonation of cement-based materials

Abstract

Abstract:In this paper, the supercritical carbonation process of cement-based materials is modelled by introducing a random porosity field to simulate the heterogeneous geometry of the carbonation profile. The suitability of two different random fields of porosity, based on the Probability Density Function (PDF) and the Ellipsoidal Autocorrelation Function (EAF) methods, are investigated, respectively, in simulating the distribution of porosity in cement mortar. After incorporating the above random fields into an established supercritical carbonation model, it is found that with some modifications, the EAF method with consideration of spatial correlation produces better simulation of the irregularities of the carbonation zones that have been observed from experimental results. It is also found that for given average porosity and coefficient of variation, the predicted average and maximum carbonation depths have much smaller coefficients of variation. The validated EAF supercritical carbonation model is then used in parametric studies that are conducted to assess the effect of various factors on the carbonation depth of the chemical process.

Experimental and statistical study on the irregularity of carbonation depth of cement mortar under supercritical condition

“…Carbonation depth is one of the most important characteristics that are used to define the extent of the chemical process taken place during carbonation. Experimental research has shown that under both natural [23] and supercritical [3,24] conditions, the boundary topography of a carbonation zone is irregular, characterized by a random distribution of depth along the boundary with distinctive maximum and minimum. However, current theoretical and numerical models are almost exclusively based on the assumption that the materials are isotropic and homogenous [25] , resulting in an uniform carbonation depth [26] .…”

“…It can be concluded that that it was the heterogeneity of cement-based materials that contributes mostly to the observed randomness [29] . This includes the presence of coarse aggregates [30,31] , the carbon dioxide gas diffusion paths caused by distribution of cracks [31,32] and the randomly distributed porosity of cement mortar [24] . To study the irregularity of carbonation depth, Huang, et al [27] found that the variation of carbonation depth increased with increased use of coarse aggregates.…”

“…Both supercritical carbonation experiments and multiphysics numerical simulations are carried out. The numerical simulations are based on the multi-physics model developed and validated previously by the authors [24] , by which random porosity of cement mortar can be considered. An image processing technique is proposed in this paper for the spectral analysis of the experimental results.…”

“…In this section, the test results presented in Section 3 are used to validate the probability density and the PSD of the carbonation depth predicted by the 2-D Multiphysics supercritical carbonation model developed previously by the authors [24] , where a random field of porosity of cement-based on the method of the modified ellipsoidal autocorrelation function was used to simulate the random voids distribution. The developed random field model of porosity offered a porosity distribution ranged from 0 to 1 and considered the following spatial correlation by selecting the values of a and b [24] .…”

“…where f is an ellipsoidal autocorrelation function; a and b are the autocorrelation lengths in the x and y directions, respectively; r is the roughness factor (when r=0, it is the Gaussian autocorrelation function). In the previous work, it was assumed that the autocorrelation lengths, a and b, in equation 8were both 0.005 m [24] . It was observed that the introduction of spatial correlation resulted in more realistic results than those from other To simulate the random nature of the carbonation front, there are three main parameters that have to be considered, including the average porosity, the autocorrelation lengths and the coefficient of variation of porosity.…”