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Article

Airflow and Particle Transport Prediction through Stenosis Airways

1
School of Mechanical and Mechatronic Engineering, University of Technology Sydney (UTS), 15 Broadway, Ultimo, NSW 2007, Australia
2
James Cook University, Australian Institute of Tropical Health and Medicine, Townsville, QLD 4810, Australia
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(3), 1119; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17031119
Received: 26 December 2019 / Revised: 7 February 2020 / Accepted: 8 February 2020 / Published: 10 February 2020
(This article belongs to the Special Issue Occupational Respiratory Health)
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. View Full-Text
Keywords: airflow; airway stenosis; lung; COPD; airway particle transport; respiration airflow; airway stenosis; lung; COPD; airway particle transport; respiration
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MDPI and ACS Style

Singh, P.; Raghav, V.; Padhmashali, V.; Paul, G.; Islam, M.S.; Saha, S.C. Airflow and Particle Transport Prediction through Stenosis Airways. Int. J. Environ. Res. Public Health 2020, 17, 1119. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17031119

AMA Style

Singh P, Raghav V, Padhmashali V, Paul G, Islam MS, Saha SC. Airflow and Particle Transport Prediction through Stenosis Airways. International Journal of Environmental Research and Public Health. 2020; 17(3):1119. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17031119

Chicago/Turabian Style

Singh, Parth, Vishnu Raghav, Vignesh Padhmashali, Gunther Paul, Mohammad S. Islam, and Suvash C. Saha 2020. "Airflow and Particle Transport Prediction through Stenosis Airways" International Journal of Environmental Research and Public Health 17, no. 3: 1119. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17031119

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