Medical & Biological Engineering & Computing

, Volume 45, Issue 9, pp 829–836 | Cite as

A computational fluid dynamics study of inspiratory flow in orotracheal geometries

  • T. P. Collins
  • G. R. TaborEmail author
  • P. G. Young
Original Article


Computational fluid dynamics (CFD) has been used to investigate the flow of air through the human orotracheal system. Results from an idealised geometry, and from a patient-specific geometry created from MRI scans were compared. The results showed a significant difference in the flow structures between the two geometries. Inert particles with diameters in the range 1–9 μm were tracked through the two geometries. Particle diameter has proved to be an important factor in defining the eventual destinations of inhaled particles. Results from our calculations match other experimental and computational results in the literature, and differences between the idealised and patient-specific geometries are less significant.


CFD Image based meshing Respiration 


  1. 1.
    Barbini A, Brighenti C, Cevenini G, Gnudi G (2005) A dynamic morphometric model of the normal lung for studying expiratory flow limitation in mechanical ventilation. Ann Biomed Eng 33(4):518–530CrossRefGoogle Scholar
  2. 2.
    Cebral JR, Löhner R (2001) From medical images to anatomically accurate finite element grids. Int J Numer Meth Eng 51:985–1008zbMATHCrossRefGoogle Scholar
  3. 3.
    Gosman AD, Ioannides E (1983) Aspects of computer simulation of liquid-fueled combustors. J Energy 7(6):482–490Google Scholar
  4. 4.
    Green A (2004) Modelling of peak-flow wall shear stress in major airways of the lung. J Biomech 37:661–667CrossRefGoogle Scholar
  5. 5.
    Heenan AF, Matilda E, Pollard A, Finlay WH (2003) Experimental measurements and computational modelling of the flow field in an idealised human oropharynx. Exp Fluids 35:70–84CrossRefGoogle Scholar
  6. 6.
    Jin HH, Fan JR, Zeng MJ, Cen KF (2007) Large eddy simulation of inhaled particle deposition within the human upper respiratory tract. J Aerosol Sci 38:257–268CrossRefGoogle Scholar
  7. 7.
    Ladak HM, Milner JS, Steinman DA (2000) Rapid three-dimensional segmentation of the carotid bifurcation from serial mr images. J Biomech Eng T ASME 122(1):96–99CrossRefGoogle Scholar
  8. 8.
    Ma B, Lutchen KA (2006) An anatomically based hybrid computational model of the human lung and its application to low frequency oscillatory mechanics. Ann Biomed Eng 34(11):1691–1704CrossRefGoogle Scholar
  9. 9.
    Mitchell J, Nagel M (2004) Particle size analysis of aerosol from medical inhalers. Kona 22:32–65Google Scholar
  10. 10.
    Morsi SA, Alexander AJ (1972) An investigation of particle trajectories in two-phase flow systems. J Fluid Mech 55(2):193–208zbMATHCrossRefGoogle Scholar
  11. 11.
    Nowak N, Kakade P, Annapragada A (2003) Computational fluid dynamics simulation of airflow and aerosol deposition in human lungs. Ann Biomed Eng 31:374–390CrossRefGoogle Scholar
  12. 12.
    Stapleton KW, Guantsch E, Hoskinson M, Finlay WH (2000) On the suitability of k−ε turbulence modelling for aerosol deposition in the mouth and throat: a comparison with experiment. J Aerosol Sci 31:739–749CrossRefGoogle Scholar
  13. 13.
    Tabor G, Young PG, Beresford-West T, Benattayallah A (2007) Mesh construction from medical imaging for multiphysics simulation: Heat transfer and fluid flow in complex geometries. Eng App Comp Fluid Mech 2(1):126–135Google Scholar
  14. 14.
    Wilcox DC (1994) Simulating transition with a two-equation turbulence model. AIAA J 32:247–255zbMATHCrossRefGoogle Scholar

Copyright information

© International Federation for Medical and Biological Engineering 2007

Authors and Affiliations

  1. 1.School of Engineering, Computer Science and MathematicsUniversity of ExeterExeterUK

Personalised recommendations