Airflow and particle transport prediction through stenosis airways

Singh, Parth, Raghav, Vishnu, Padhmashali, Vignesh, Paul, Gunther, Islam, Mohammad S., and Saha, Suvash C. (2020) Airflow and particle transport prediction through stenosis airways. International Journal of Environmental Research and Public Health, 17 (3). 1119.

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Abstract

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.

Item ID: 62244
Item Type: Article (Research - C1)
ISSN: 1660-4601
Keywords: airflow; airway stenosis; lung; COPD; airway particle transport; respiration
Copyright Information: © 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/).
Funders: University of Technology Sydney (UTS)
Projects and Grants: UTS grant number PR019-8377, UTS grant number BlueSky-2232433
Date Deposited: 12 Feb 2020 02:35
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460207 Modelling and simulation @ 50%
32 BIOMEDICAL AND CLINICAL SCIENCES > 3201 Cardiovascular medicine and haematology > 320103 Respiratory diseases @ 50%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920115 Respiratory System and Diseases (incl. Asthma) @ 50%
97 EXPANDING KNOWLEDGE > 970111 Expanding Knowledge in the Medical and Health Sciences @ 50%
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