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  • 标题:Euler-Lagrange Prediction of Diesel-Exhaust Polydisperse Particle Transport and Deposition in Lung: Anatomy and Turbulence Effects
  • 本地全文:下载
  • 作者:Mohammad S. Islam ; Suvash C. Saha ; Tevfik Gemci
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2019
  • 卷号:9
  • 期号:1
  • 页码:1-16
  • DOI:10.1038/s41598-019-48753-6
  • 出版社:Springer Nature
  • 摘要:In clinical assessments, the correlation between atmospheric air pollution and respiratory damage is highly complicated. Epidemiological studies show that atmospheric air pollution is largely responsible for the global proliferation of pulmonary disease. This is particularly significant, since most Computational Fluid Dynamics (CFD) studies to date have used monodisperse particles, which may not accurately reflect realistic inhalation patterns, since atmospheric aerosols are mostly polydisperse. The aim of this study is to investigate the anatomy and turbulent effects on polydisperse particle transport and deposition (TD) in the upper airways. The Euler-Lagrange approach is used for polydisperse particle TD prediction in both laminar and turbulent conditions. Various anatomical models are adopted to investigate the polydisperse particle TD under different flow conditions. Rossin-Rammler diameter distribution is used for the distribution of the initial particle diameter. The numerical results illustrate that airflow rate distribution at the right lung of a realistic model is higher than a non-realistic model. The CFD study also shows that turbulence effects on deposition are higher for larger diameter particles than with particles of smaller diameter. A significant amount of polydisperse particles are also shown to be deposited at the tracheal wall for CT-based model, whereas particles are mostly deposited at the carinal angle for the non-realistic model. A comprehensive, polydisperse particle TD analysis would enhance understanding of the realistic deposition pattern and decrease unwanted therapeutic aerosol deposition at the extrathoracic airways.
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