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Modeling pressure drop values across ultra-thin nanofiber filters with various ranges of filtration parameters under an aerodynamic slip effect

Computational fluid dynamics simulations of fibrous filters with 56 combinations of different fiber sizes, packing densities, face velocities, and thicknesses were conducted for developing models that predict pressure drops across nanofiber filters. The accuracy of the simulation method was confirme...

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Detalles Bibliográficos
Autores principales: Lee, Songhui, Bui-Vinh, Dai, Baek, Minwoo, Kwak, Dong-Bin, Lee, Handol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10070425/
https://www.ncbi.nlm.nih.gov/pubmed/37012373
http://dx.doi.org/10.1038/s41598-023-32765-4
Descripción
Sumario:Computational fluid dynamics simulations of fibrous filters with 56 combinations of different fiber sizes, packing densities, face velocities, and thicknesses were conducted for developing models that predict pressure drops across nanofiber filters. The accuracy of the simulation method was confirmed by comparing the numerical pressure drops to the experimental data obtained for polyacrylonitrile electrospun nanofiber filters. In the simulations, an aerodynamic slip effect around the surface of the small nanofibers was considered. The results showed that, unlike in the case of conventional filtration theory, pressure drops across the thin layers of electrospun nanofiber filters are not proportional to the thickness. This might be a critical factor for obtaining precise pressure drops across the electrospun nanofiber filters with extremely thin layers. Finally, we derived the product of drag coefficient and Reynolds number as a function of packing density, Knudsen number, and ratio of thickness to fiber diameter to get the correlation equation for pressure drop prediction. The obtained equation predicted the pressure drops across the nanofiber filters with the maximum relative difference of less than 15%.