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Filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks
Facemasks have become important tools to fight virus spread during the recent COVID-19 pandemic, but their effectiveness is still under debate. We present a computational model to predict the filtering efficiency of an N95-facemask, consisting of three non-woven fiber layers with different particle...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8558106/ https://www.ncbi.nlm.nih.gov/pubmed/34744488 http://dx.doi.org/10.1016/j.seppur.2021.120049 |
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author | Borgelink, B.T.H. Carchia, A.E. Hernández-Sánchez, J.F. Caputo, D. Gardeniers, J.G.E. Susarrey-Arce, A. |
author_facet | Borgelink, B.T.H. Carchia, A.E. Hernández-Sánchez, J.F. Caputo, D. Gardeniers, J.G.E. Susarrey-Arce, A. |
author_sort | Borgelink, B.T.H. |
collection | PubMed |
description | Facemasks have become important tools to fight virus spread during the recent COVID-19 pandemic, but their effectiveness is still under debate. We present a computational model to predict the filtering efficiency of an N95-facemask, consisting of three non-woven fiber layers with different particle capturing mechanisms. Parameters such as fiber layer thickness, diameter distribution, and packing density are used to construct two-dimensional cross-sectional geometries. An essential and novel element is that the polydisperse fibers are positioned randomly within a simulation domain, and that the simulation is repeated with different random configurations. This strategy is thought to give a more realistic view of practical facemasks compared to existing analytical models that mostly assume homogeneous fiber beds of monodisperse fibers. The incompressible Navier-Stokes and continuity equations are used to solve the velocity field for various droplet-laden air inflow velocities. Droplet diameters are ranging from 10 nm to 1.0 µm, which covers the size range from the SARS-CoV-2 virus to the large virus-laden airborne droplets. Air inflow velocities varying between 0.1 m·s(−1) to 10 m·s(−1) are considered, which are typically encountered during expiratory events like breathing, talking, and coughing. The presented model elucidates the different capturing efficiencies (i.e., mechanical and electrostatic filtering) of droplets as a function of their diameter and air inflow velocity. Simulation results are compared to analytical models and particularly compare well with experimental results from literature. Our numerical approach will be helpful in finding new directions for anti-viral facemask optimization. |
format | Online Article Text |
id | pubmed-8558106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Authors. Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85581062021-11-01 Filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks Borgelink, B.T.H. Carchia, A.E. Hernández-Sánchez, J.F. Caputo, D. Gardeniers, J.G.E. Susarrey-Arce, A. Sep Purif Technol Article Facemasks have become important tools to fight virus spread during the recent COVID-19 pandemic, but their effectiveness is still under debate. We present a computational model to predict the filtering efficiency of an N95-facemask, consisting of three non-woven fiber layers with different particle capturing mechanisms. Parameters such as fiber layer thickness, diameter distribution, and packing density are used to construct two-dimensional cross-sectional geometries. An essential and novel element is that the polydisperse fibers are positioned randomly within a simulation domain, and that the simulation is repeated with different random configurations. This strategy is thought to give a more realistic view of practical facemasks compared to existing analytical models that mostly assume homogeneous fiber beds of monodisperse fibers. The incompressible Navier-Stokes and continuity equations are used to solve the velocity field for various droplet-laden air inflow velocities. Droplet diameters are ranging from 10 nm to 1.0 µm, which covers the size range from the SARS-CoV-2 virus to the large virus-laden airborne droplets. Air inflow velocities varying between 0.1 m·s(−1) to 10 m·s(−1) are considered, which are typically encountered during expiratory events like breathing, talking, and coughing. The presented model elucidates the different capturing efficiencies (i.e., mechanical and electrostatic filtering) of droplets as a function of their diameter and air inflow velocity. Simulation results are compared to analytical models and particularly compare well with experimental results from literature. Our numerical approach will be helpful in finding new directions for anti-viral facemask optimization. The Authors. Published by Elsevier B.V. 2022-02-01 2021-11-01 /pmc/articles/PMC8558106/ /pubmed/34744488 http://dx.doi.org/10.1016/j.seppur.2021.120049 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Borgelink, B.T.H. Carchia, A.E. Hernández-Sánchez, J.F. Caputo, D. Gardeniers, J.G.E. Susarrey-Arce, A. Filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks |
title | Filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks |
title_full | Filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks |
title_fullStr | Filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks |
title_full_unstemmed | Filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks |
title_short | Filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks |
title_sort | filtering efficiency model that includes the statistical randomness of non-woven fiber layers in facemasks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8558106/ https://www.ncbi.nlm.nih.gov/pubmed/34744488 http://dx.doi.org/10.1016/j.seppur.2021.120049 |
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