Computer Methods in Biomechanics and Biomedical Engineering | 2021

Transport and deposition of ultrafine particles in the upper tracheobronchial tree: a comparative study between approximate and realistic respiratory tract models

 
 
 
 

Abstract


Abstract This paper presents a computational fluid dynamics (CFD) study of air-particle flows in the upper tracheobronchial tree. Two respiratory tract models, including a parametrically controlled approximate airway model developed by Kitaoka (KG model) and a CT-based patient specific airway (realistic model) were used. Assuming laminar, quasi-steady, three-dimensional air flow and spherical non-interacting ultrafine particles in sequentially bifurcating rigid bronchial airways, airflow patterns and particle transport/deposition in these two airway models were evaluated and compared. Overall deposition efficiency data was compared with the widely adopted ICRP data published by The International Commission on Radiological Protection. Good deposition efficiency agreements were observed between the present respiratory tract models and the ICRP data, which validated the numerical prediction accuracy of the present computational fluid-particle dynamics (CFPD) model. For the two respiratory models, the comparison showed both difference and similarity between the approximate KG model and the realistic model. Specifically, the realistic model showed more complicated airflow patterns due to the increased surface irregularity. The deposition efficiency data revealed a deposition preference in the first-generation airways compared to the rest regions. For ultrafine particles smaller than 10\u2009nm, Brownian diffusion remains the dominant particle deposition mechanism. However, for ultrafine particles with size ranging from 10\u2009nm to 100\u2009nm, the deposition efficiency decreased dramatically with the 100\u2009nm particles approaching to zero deposition in the present bronchial tree scope. The generation-by-generation deposition data presented in this paper is indispensable to the formulation of new lung inhalation exposure models.

Volume 24
Pages 1125 - 1135
DOI 10.1080/10255842.2020.1869220
Language English
Journal Computer Methods in Biomechanics and Biomedical Engineering

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