Multiscale digital-image driven stochastic finite element modeling of chloride diffusion in recycled aggregate concrete

For estimation of the durability of recycled aggregate concrete (RAC) in chloride-rich environment, it is valuable to investigate the chloride diffusivity in RAC. Because RAC is highly heterogenous, an ideal five-phase model was designated as the representative research object of RAC in this paper. To investigate the effect of micro-scale randomness on the meso-scale chloride diffusivity in RAC, this paper developed a multiscale digital-image driven stochastic method, in which the digital-image covariance kernel was used in the Karhunen-Loeve expansion to generate basis functions for the model. The proposed method was at the first time used to analyze chloride ion diffusion in RAC. Through a couple of numerical experiments, it is indicated that the effects of aggregate shape, aggregate size and the thickness of interfacial transition zones (ITZs) are considerable on the coefficient of variation of chloride diffusivity in RAC. It is also found that the digital image kernel is more sensitive about noise than other standard covariance kernels.