Stochastic lattice discrete particle modeling of fracture in pervious concrete

Abstract

AbstractThis article presents a stochastic modeling approach for simulating the mechanical behavior of pervious concrete, based on novel extensions of the lattice discrete particle model. Selected digital images of the internal mesostructure, obtained from physical specimens, are used to survey material features and produce statistically representative descriptions of the pore networks. A procedure for estimating the statistical features of the mesostructure is proposed, and samples of a spatially correlated random field are utilized to numerically reproduce the distribution of the large, connected pores in the material. The numerical samples are linked to the topology of the lattice network by means of two novel techniques proposed herein: (1) a random placement procedure for the poly‐sized spheres representing coarse aggregate and (2) a ray tracing technique, which is used to evaluate the effective distributions of mass, stiffness, and strength of each lattice element according to the local distribution of porosity. Numerical results demonstrate how the proposed model is capable of simulating both the large scatter in strength and the variety of failure modes that are observed when testing physical specimens of pervious concrete. The proposed procedure is generally applicable to different types of materials with varying porosity, opening up new possibilities for the simulation of porous media by means of lattice discrete particle modeling techniques.