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Simulation of particulate matter transport and deposition in the airway of COVID-19 patients


Citation

Zhu, Di (2024) Simulation of particulate matter transport and deposition in the airway of COVID-19 patients. Doctoral thesis, Universiti Putra Malaysia.

Abstract

COVID-19 is one of the greatest challenges facing mankind in recent years, with more than 600 million people infected with COVID-19 to date, and with secondary and tertiary infections to date, COVID-19 is mutating and putting human life at risk. The effects of COVID-19 on the lungs of humans are significant. And the lung symptoms are consistent as well as universal. Patients with lung disease caused by COVID-19 and its morbidity have a high mortality rate from COVID-19. The problem of air pollution has become increasingly serious in recent years. Airborne PM is one of the culprits of respiratory diseases. PM causes most respiratory diseases. It has been shown that COVID-19 patients with underlying respiratory diseases have significantly higher mortality and critical rates than normal patients. Therefore, it is important to study the deposition and movement of PM in the respiratory system of patients with COVID-19, which will be of value in the study of inhaled drugs for the treatment of patients with COVID-19. The main objective of this paper is to study the deposition as well as movement of PM in the human respiratory system. It will provide some value for the future study of the effect of mutated COVID-19 virus on the human body. In this paper, the deposition as well as the movement of particulate matter in the human respiratory system is investigated by using the computational fluid dynamics method, and the three-dimensional model of the human airway is reconstructed by CT scanning of COVID-19, using the CT scanning images as the basis for reconstructing the human airway using Mimics software. And the model was imported into ANSYS Workbench 2021R1 for simulation. At the same time, the Low Reynolds factor k-ε model was used to solve the airflow field, and the Lagrangian particle tracer hair was used to describe the trajectory of the respirable particles. In order to understand the deposition and movement of particles in different scenarios, we set different values for the respiratory intensity and particle size. In this paper, we simulated the deposition and movement of particles in the airways of patients with COVID-19 and normal subjects under four respiratory intensities, namely, 15L/min, 30L/min, and 60L/min, and five particle sizes, namely, 0.1μm, 1μm, 2.5 m, 5μm, and 10μm. The deposition and movement of particulate matter in the airways of COVID-19 patients under these five conditions. The results show that the deposition rate of particles increases with the increase of respiratory intensity. When the particle size is greater than 2.5 microns, the deposition rate of particles with a respiratory intensity of 60L/min is the highest; when the particle size is less than 1 micron, the deposition rate of particles with a respiratory intensity of 60L/min is the lowest; when the particle size is 1-2.5 microns, the deposition rate of particles with a respiratory intensity of 15L/min is the lowest. The study found that the deposition of particulate matter was minimal when patients with COVID-19 took the prone sleeping position, and the prone sleeping position was more suitable for patients with COVID-19.


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Official URL or Download Paper: http://ethesis.upm.edu.my/id/eprint/19018

Additional Metadata

Item Type: Thesis (Doctoral)
Subject: COVID-19 (Disease) - Transmission
Subject: Respiratory organs - Pathophysiology
Call Number: FK 2024 53
Chairman Supervisor: Professor Ir. Kamarul Arifin bin Ahmad
Divisions: Faculty of Engineering
Keywords: CFD; COVID-19; Deposition of Particulates; Transport of Respirable Particulates; Mimics; 3D models
Sustainable Development Goals (SDGs): GOAL 3: Good Health and Well-being
Depositing User: Pelajar Latihan Industri
Date Deposited: 14 Jul 2026 03:28
Last Modified: 14 Jul 2026 03:28
URI: http://psasir.upm.edu.my/id/eprint/125970
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