4.3 Article

Numerical simulation of airflow and microparticle deposition in a synchrotron micro-CT-based pulmonary acinus model

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/10255842.2014.915030

关键词

particle deposition; synchrotron radiation-CT; pulmonary acinus; computational fluid dynamics

资金

  1. Program Review of SPring-8 [2007A2071]
  2. Japan Society for the Promotion of Science [19700394]
  3. Grants-in-Aid for Scientific Research [25560428, 26280110, 19700394] Funding Source: KAKEN

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The acinus consists of complex, branched alveolar ducts and numerous surrounding alveoli, and so in this study, we hypothesized that the particle deposition can be much influenced by the complex acinar geometry, and simulated the airflow and particle deposition (density=1.0g/cm(3), diameter=1 and 3 mu m) numerically in a pulmonary acinar model based on synchrotron micro-CT of the mammalian lung. We assumed that the fluid-structure interaction was neglected and that alveolar flow was induced by the expansion and contraction of the acinar model with the volume changing sinusoidally with time as the moving boundary conditions. The alveolar flow was dominated by radial flows, and a weak recirculating flow was observed at the proximal side of alveoli during the entire respiratory cycle, despite the maximum Reynolds number at the inlet being 0.029. Under zero gravity, the particle deposition rate after single breathing was less than 0.01, although the particles were transported deeply into the acinus after inspiration. Under a gravitational field, the deposition rate and map were influenced strongly by gravity orientation. In the case of a particle diameter of 1 mu m, the rate increased dramatically and mostly non-deposited particles remained in the model, indicating that the rate would increase further after repeated breathing. At a particle diameter of 3 mu m, the rate was 1.0 and all particles were deposited during single breathing. Our results show that the particle deposition rate in realistic pulmonary acinar model is higher than in an idealized model.

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