Computational characterization of nonwoven fiber materials: Predicting permeability from pore-space morphology

Nonwoven fibrous membranes are widely used as filtration media, and tailoring the microstructure of the pore space is a key to improving filtration efficiency. In this contribution, we present a computational framework for generating realistic random fibrous media with a wide range of porosities and systematically analyze the effect of pore size distribution on permeability and tortuosity. Combining the pore-network statistical analysis with pore-scale flow simulations reveals the influence of the statistical pore size distribution on the effective fluid transport properties over a wide range of macroscopic porosities. The computational framework is applicable to segmentation of experimental imaging techniques such as X-ray computed tomography or scanning electron microscopy and thus enables rapid characterization and design of porous media with tailored properties for filtration and separation applications.