Computational Modeling of Cough Droplet Behavior in the Human Upper Respiratory AirwaySource: Journal of Engineering and Science in Medical Diagnostics and Therapy:;2024:;volume( 008 ):;issue: 003::page 31007-1DOI: 10.1115/1.4066625Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This study investigated the interaction of cough droplets with airflow in a realistic human airway. The ultimate aim was to understand the behavior of cough droplets inside the airway and to assess the potential of droplets to be retained in the airway or transmitted to the lungs. A computational fluid dynamics (CFD) model, based on the Euler–Lagrangian framework, was employed to predict the two-phase, droplet-laden transient cough flow in a realistic three-dimensional (3D) human airway. The airway geometry was reconstructed from patient computed tomography (CT) scan dataset. The discrete phase model was used to track the motion of the droplets in the air flow. Two distinct cough profiles—a strong cough and a weak cough—acquired experimentally from human subjects, were used as input to simulate normal and disordered cough functions. The effects of cough strength and droplet size on droplet retention and aspiration in the airway were investigated. It was found that droplet retention was significantly higher for a weak cough compared to a strong cough. For a weak cough, the highest droplet retention percentage exceeded 60%, while for a strong cough, it was less than 20%. Larger sized droplets were more likely to be aspirated into the lungs, especially under weak cough conditions. In the case of weak cough, more than 5% of the 200 μm sized droplets were aspirated into the lungs, whereas for strong cough, aspiration was less than 2%.
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contributor author | Khan, Rafid Jahangir | |
contributor author | Ilegbusi, Olusegun | |
date accessioned | 2025-04-21T10:19:20Z | |
date available | 2025-04-21T10:19:20Z | |
date copyright | 10/23/2024 12:00:00 AM | |
date issued | 2024 | |
identifier issn | 2572-7958 | |
identifier other | jesmdt_008_03_031007.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4305939 | |
description abstract | This study investigated the interaction of cough droplets with airflow in a realistic human airway. The ultimate aim was to understand the behavior of cough droplets inside the airway and to assess the potential of droplets to be retained in the airway or transmitted to the lungs. A computational fluid dynamics (CFD) model, based on the Euler–Lagrangian framework, was employed to predict the two-phase, droplet-laden transient cough flow in a realistic three-dimensional (3D) human airway. The airway geometry was reconstructed from patient computed tomography (CT) scan dataset. The discrete phase model was used to track the motion of the droplets in the air flow. Two distinct cough profiles—a strong cough and a weak cough—acquired experimentally from human subjects, were used as input to simulate normal and disordered cough functions. The effects of cough strength and droplet size on droplet retention and aspiration in the airway were investigated. It was found that droplet retention was significantly higher for a weak cough compared to a strong cough. For a weak cough, the highest droplet retention percentage exceeded 60%, while for a strong cough, it was less than 20%. Larger sized droplets were more likely to be aspirated into the lungs, especially under weak cough conditions. In the case of weak cough, more than 5% of the 200 μm sized droplets were aspirated into the lungs, whereas for strong cough, aspiration was less than 2%. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Computational Modeling of Cough Droplet Behavior in the Human Upper Respiratory Airway | |
type | Journal Paper | |
journal volume | 8 | |
journal issue | 3 | |
journal title | Journal of Engineering and Science in Medical Diagnostics and Therapy | |
identifier doi | 10.1115/1.4066625 | |
journal fristpage | 31007-1 | |
journal lastpage | 31007-9 | |
page | 9 | |
tree | Journal of Engineering and Science in Medical Diagnostics and Therapy:;2024:;volume( 008 ):;issue: 003 | |
contenttype | Fulltext |