Permeability prediction of fibrous porous media by the lattice Boltzmann method with a fluid-structure boundary reconstruction scheme
Source abstract
Abstract
The D3Q27 lattice Boltzmann method (LBM) combined with the fluid-structure boundary reconstruction (fsBR) scheme and the interpolated bounce back (IPBB) method is extensively evaluated to predict the permeability of nonwoven fibrous porous media. The fsBR-IPBB method transfers digitally defined step-like boundary data, e.g. the three-dimensional structure data obtained by the X-ray computed tomography, to continuous smooth boundary data via level-set functions. It leads to highly accurate calculations despite low lattice resolutions of thin fibers with circular cross-sectional shapes, compared to the conventional half-way bounce back (HWBB) method. The fsBR-IPBB method is first applied to predict the permeability of two different arrays of impermeable circular cylinders and verified by comparing the results with the data in the literature. We then validate the method referring to the numerically and experimentally obtained permeability of six types of nonwoven fabrics prepared by the industrial hydroentanglement process. Finally, the discussion on the applicability and the limitation of the macroscopic correlation models to estimate permeability of porous media is carried out. The results show that although the calculated permeability is in reasonable agreement with the measured one with an error of 8.1–16.3%, analytical or empirical correlation models fail to give the correct trend due to the highly inhomogeneous and anisotropic properties of hydroentangled nonwoven fabrics.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Lattice Boltzmann Simulation Studies · Aerosol Filtration and Electrostatic Precipitation · Textile materials and evaluations
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical Engineering, Osaka Prefecture University, Sakai, Osaka, Japan
Department of Computer Aided Engineering, Asahi-Kasei Corporation, Kawasaki, Kanagawa, Japan
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