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Computational fluid dynamic models as tools to predict aerosol distribution in tracheobronchial airways

Claudia Atzeni1, Gianluca Lesma1, Gabriele Dubini1, Maurizio Masi2, Filippo Rossi2, Elena Bianchi1*

 

Author Information

  1. Laboratory of Biological Structures Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, Politecnico Di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
  2. epartment of Chemistry, Materials and Chemical Engineering "Giulio Natta", Politecnico Di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy. *email: elena1.bianchi@polimi.it

 

Abstract

Aerosol and pollutants, in form of particulates 5–8 μm in main size face every day our respiratory system as natural suspension in air or forced to be inhaled as a coadjutant in a medical therapy for respiratory diseases. This inhalation happens in children to elderly, women and men, healthy or sick and disable people. In this paper we analyzed the inhalation of aerosol in conditions assimilable to the thermal therapy. We use a computational fluid dynamic 3D model to compute and visualize the trajectories of aerosol (3–7–10–25 µm) down to the sixth generation of bronchi, in a steady and dynamic condition (7 µm) set as breath cycle at rest. Results, compared to a set of milestone experimental studies published in literature, allow the comprehension of particles behavior during the inhalation from mouth to bronchi sixth generation, the visualization of jet at larynx constriction and vortices, in an averaged characteristic rigorous geometrical model including tracheal rings. Results on trajectories and deposition show the importance of the including transient physiological breath cycle on aerosol deposition analyses. Numerical and graphical results, may enable the design of medical devices and protocols to make the inhalations more effective in all the users’ population.

 

Keywords

Anatomy - Health care - Medical research

Ricerca pubblicata su:
Scientific Reports

Titolo originale:
Computational fluid dynamic models as tools to predict aerosol distribution in tracheobronchial airways

Anno di pubblicazione:
2021

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