Experimental and numerical study of size effect on long-term drying behavior of concrete: influence of drying depth

This paper presents both experimental study and multi-physics modelling of supercritical carbonation of concrete. A novel mathematical model is proposed to simulate random distribution of coarse aggregates in concrete. Supercritical carbonation tests of concrete are carried out and the measured carbonation depth is compared with the simulation results. On the basis of previous research on random field of porosity and supercritical carbonation of cement mortar, a new supercritical carbonation model is developed to study the effect of randomly distributed coarse aggregates and porosity on the irregularities of carbonation depth of concrete. The effect of the type, volume fraction and gradation of coarse aggregates and the porosity of ITZ on the distribution of irregular carbonation depth are also studied. The results demonstrate that the proposed twodimensional random coarse aggregates model can be used satisfactorily to generate different types, volume fraction and gradation of coarse aggregates with the designed mix proportion within a confined space. The method provides a better and more realistic predictive model for simulating carbonation depth of concrete due to random distribution of coarse aggregates and porosity.

Section: Introductionmentioning

confidence: 99%

Experimental study and multi-physics modelling of concrete under supercritical carbonation

et al. 2019

“…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] . There are very limited research on the irregularities of carbonation depth, including Huang, et al [27] and Ruan, et al [28] 's studies on the carbonation process of concrete where a non-uniform distribution of carbonation depth was observed by considering the influence of aggregates.…”

Section: Introductionmentioning

confidence: 99%

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

Liu

et al. 2018

The heterogeneity of a cement-based material results in a random spatial distribution of carbonation depth. Currently, there is a lack of both experimental and numerical investigations aiming at a statistical understanding of this important phenomenon. This paper presents both experimental and numerical supercritical carbonation test results of cement mortar blocks. The carbonation depths are measured along the carbonation boundary by the proposed rapid image processing technique, which are then statistically studied by calculating, e.g., their probability density and power spectral density (PSD). The results indicate that the distribution of the carbonation depth can be approximately represented by a lognormal distribution function and the PSD has quantitative correlation with some of the statistic parameters used in the simulations. In particular, the effects of the autocorrelation lengths and the coefficient of variation of porosity, which are used to define the random porosity field, on the irregularity of carbonation depth are analyzed numerically in details and validated by experimental results. The study has shown that using a random field of porosity with due consideration of spatial correlation and variance, the irregularity of carbonation depth can be realistically captured by the numerical model. The numerical results confirm that lognormal distributions represent the random nature of carbonation depth well and the average and variance of the irregular carbonation depth increase with the increase of carbonation time, autocorrelation length and coefficient of variation of porosity. The study also offers a potential method to numerically calibrate some of the statistic parameters required by a numerical carbonation model through comparing the PSD with that from experimental tests. Overall the methodology adopted in the paper can provide a foundation for future investigations on probability analysis of carbonation depth and other similar work based on multi-scale and-physics modelling.

“…However, current theoretical and numerical models are almost exclusively based on the assumption that the materials are isotropic and homogenous [20] , resulting in an average carbonation depth [20] . In practical applications, it is the maximum, rather than the average, carbonation depth that is critical in, e,g., reinforcement corrosion analysis.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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.