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Airflow and Particle Transport Prediction through Stenosis Airways

Airflow and particle transport in the human lung system is influenced by biological and other factors such as breathing pattern, particle properties, and deposition mechanisms. Most of the studies to date have analyzed airflow characterization and aerosol transport in idealized and realistic models....

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Autores principales: Singh, Parth, Raghav, Vishnu, Padhmashali, Vignesh, Paul, Gunther, Islam, Mohammad S., Saha, Suvash C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037172/
https://www.ncbi.nlm.nih.gov/pubmed/32050584
http://dx.doi.org/10.3390/ijerph17031119
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author Singh, Parth
Raghav, Vishnu
Padhmashali, Vignesh
Paul, Gunther
Islam, Mohammad S.
Saha, Suvash C.
author_facet Singh, Parth
Raghav, Vishnu
Padhmashali, Vignesh
Paul, Gunther
Islam, Mohammad S.
Saha, Suvash C.
author_sort Singh, Parth
collection PubMed
description Airflow and particle transport in the human lung system is influenced by biological and other factors such as breathing pattern, particle properties, and deposition mechanisms. Most of the studies to date have analyzed airflow characterization and aerosol transport in idealized and realistic models. Precise airflow characterization for airway stenosis in a digital reference model is lacking in the literature. This study presents a numerical simulation of airflow and particle transport through a stenosis section of the airway. A realistic CT-scan-based mouth–throat and upper airway model was used for the numerical calculations. Three different models of a healthy lung and of airway stenosis of the left and right lung were used for the calculations. The ANSYS FLUENT solver, based on the finite volume discretization technique, was used as a numerical tool. Proper grid refinement and validation were performed. The numerical results show a complex-velocity flow field for airway stenosis, where airflow velocity magnitude at the stenosis section was found to be higher than that in healthy airways. Pressure drops at the mouth–throat and in the upper airways show a nonlinear trend. Comprehensive pressure analysis of stenosis airways would increase our knowledge of the safe mechanical ventilation of the lung. The turbulence intensities at the stenosis sections of the right and left lung were found to be different. Deposition efficiency (DE) increased with flow rate and particle size. The findings of the present study increase our understanding of airflow patterns in airway stenosis under various disease conditions. More comprehensive stenosis analysis is required to further improve knowledge of the field.
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spelling pubmed-70371722020-03-11 Airflow and Particle Transport Prediction through Stenosis Airways Singh, Parth Raghav, Vishnu Padhmashali, Vignesh Paul, Gunther Islam, Mohammad S. Saha, Suvash C. Int J Environ Res Public Health Article Airflow and particle transport in the human lung system is influenced by biological and other factors such as breathing pattern, particle properties, and deposition mechanisms. Most of the studies to date have analyzed airflow characterization and aerosol transport in idealized and realistic models. Precise airflow characterization for airway stenosis in a digital reference model is lacking in the literature. This study presents a numerical simulation of airflow and particle transport through a stenosis section of the airway. A realistic CT-scan-based mouth–throat and upper airway model was used for the numerical calculations. Three different models of a healthy lung and of airway stenosis of the left and right lung were used for the calculations. The ANSYS FLUENT solver, based on the finite volume discretization technique, was used as a numerical tool. Proper grid refinement and validation were performed. The numerical results show a complex-velocity flow field for airway stenosis, where airflow velocity magnitude at the stenosis section was found to be higher than that in healthy airways. Pressure drops at the mouth–throat and in the upper airways show a nonlinear trend. Comprehensive pressure analysis of stenosis airways would increase our knowledge of the safe mechanical ventilation of the lung. The turbulence intensities at the stenosis sections of the right and left lung were found to be different. Deposition efficiency (DE) increased with flow rate and particle size. The findings of the present study increase our understanding of airflow patterns in airway stenosis under various disease conditions. More comprehensive stenosis analysis is required to further improve knowledge of the field. MDPI 2020-02-10 2020-02 /pmc/articles/PMC7037172/ /pubmed/32050584 http://dx.doi.org/10.3390/ijerph17031119 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Singh, Parth
Raghav, Vishnu
Padhmashali, Vignesh
Paul, Gunther
Islam, Mohammad S.
Saha, Suvash C.
Airflow and Particle Transport Prediction through Stenosis Airways
title Airflow and Particle Transport Prediction through Stenosis Airways
title_full Airflow and Particle Transport Prediction through Stenosis Airways
title_fullStr Airflow and Particle Transport Prediction through Stenosis Airways
title_full_unstemmed Airflow and Particle Transport Prediction through Stenosis Airways
title_short Airflow and Particle Transport Prediction through Stenosis Airways
title_sort airflow and particle transport prediction through stenosis airways
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037172/
https://www.ncbi.nlm.nih.gov/pubmed/32050584
http://dx.doi.org/10.3390/ijerph17031119
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