Estimation of the probability of finite percolation in porous microstructures from tomographic images

Abstract

AbstractPercolation is an important property of porous media, as it describes the connectivity of pores. We propose a novel, direction-dependent percolation probability which can be efficiently estimated from three-dimensional images obtained by microtomography. Furthermore, in order to describe the penetrability of the pore space by particles of a given diameter or a fluid of a given surface tension, we introduce a percolation probability depending on the width of the pores, from which we may also derive a measure of the mean pore channel width. As application examples, we consider the penetrability of porous beryllium pebbles, the connectivity of pores in arctic firn, the percolation of the pore space of aluminum foams and the mean width of the percolating space between the fibers in a laminate's percolating pore space.