Computational Modeling of Multiscale Air Filter Media Consisting of Nano- and Microfibers

Abstract

With regard to air filtration, computational work has been performed to predict filter performance outcomes in different particulate scenarios, yet comparative verification of different modeling methods is rarely studied. In this study, computational simulations with different modeling techniques are demonstrated for filter media with various fiber diameters, thicknesses, and basis weights. For a microscale meltblown (Micro) filter web, a resolved model reconstructed by X-ray micro-computed tomography (Xμ-CT) is generated. The representative volume elements and the number of voxels are determined by examining the simulation accuracy and the computational time. For a multiscale dual-layer web composed of nanofibers (Nano) and microscale spunbond fibers (SB), a parametric model and a porous plane model are generated. The accuracy of the models is verified in terms of the morphological parameters and flow resistance in comparison, with actual test results. The parametric model and porous plane model suitably predict the characteristics of multiscale filter media. Simulated filtration is conducted for particles of different sizes (0.05–1 μm) in an effort to understand the relationships among the filter morphology, face velocity (71 and 142 mm/s), and particle size. This study presents relevant modeling methods, specifically a resolved model, a parametric model, and a porous plane model for virtualizing filter media on various scales. It provides an informative discussion of various modeling parameters for accurate predictions of filtering behaviors with potential applicability to the reverse-engineering of filter products.