Simulating permeabilities based on 3D image data of a layered nano-porous membrane

The macroscopic properties of materials are strongly influenced by their microstructure. Essential micro-structural information can be obtained from high-resolution 3D images, usually obtained by computed tomography. Here, a layered nano-porous ZrO2 Al2O3 membrane for fluid filtration is investigated, whose two finer layers can not be resolved properly by computed tomography. 3D image data of these structures are therefore obtained by the combination of focused ion beam sectioning and scanning electron microscopy. Reconstruction of porous structures from this type of image data and subsequent numerical simulation of flow properties within the reconstructed structure bear several sources of error. Using stochastic geometry models for the solid component, we examine more closely the error due to the typical anisotropic voxel setting as well as the error due to the also typical uneven sample shape.