Annals of Biomedical Engineering

, Volume 40, Issue 7, pp 1495–1507 | Cite as

Effect of Carrier Gas Properties on Aerosol Distribution in a CT-based Human Airway Numerical Model

  • Shinjiro Miyawaki
  • Merryn H. Tawhai
  • Eric A. Hoffman
  • Ching-Long Lin


The effect of carrier gas properties on particle transport in the human lung is investigated numerically in an imaging based airway model. The airway model consists of multi-detector row computed tomography (MDCT)-based upper and intra-thoracic central airways. The large-eddy simulation technique is adopted for simulation of transitional and turbulent flows. The image-registration-derived boundary condition is employed to match regional ventilation of the whole lung. Four different carrier gases of helium (He), a helium–oxygen mixture (He–O2), air, and a xenon–oxygen mixture (Xe–O2) are considered. A steady inspiratory flow rate of 342 mL/s is imposed at the mouthpiece inlet to mimic aerosol delivery on inspiration, resulting in the Reynolds number at the trachea of Ret ≈ 190, 460, 1300, and 2800 for the respective gases of He, He–O2, air, and Xe–O2. Thus, the flow for the He case is laminar, transitional for He–O2, and turbulent for air and Xe–O2. The instantaneous and time-averaged flow fields and the laminar/transitional/turbulent characteristics resulting from the four gases are discussed. With increasing Ret, the high-speed jet formed at the glottal constriction is more dispersed around the peripheral region of the jet and its length becomes shorter. In the laminar flow the distribution of 2.5-μm particles in the central airways depends on the particle release location at the mouthpiece inlet, whereas in the turbulent flow the particles are well mixed before reaching the first bifurcation and their distribution is strongly correlated with regional ventilation.


Regional particle distribution Helium Helium–oxygen mixture Air Xenon–oxygen mixture Laminar flow Transitional flow Turbulent flow 



This work was supported in part by NIH grants R01-HL094315, R01-HL064368, R01-EB005823, and S10-RR022421. The authors are grateful to Youbing Yin, Jiwoong Choi, and Haribalan Kumar for generating meshes and CT images of the airway model, assisting with the flow simulation, and assisting with the particle simulation respectively. We also thank the San Diego Supercomputer Center (SDSC), the Texas Advanced Computing Center (TACC), and XSEDE sponsored by the National Science Foundation for the computer time.


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Copyright information

© Biomedical Engineering Society 2012

Authors and Affiliations

  • Shinjiro Miyawaki
    • 1
    • 3
  • Merryn H. Tawhai
    • 7
  • Eric A. Hoffman
    • 4
    • 5
    • 6
  • Ching-Long Lin
    • 2
    • 3
  1. 1.Department of Civil and Environmental EngineeringThe University of IowaIowa CityUSA
  2. 2.Department of Mechanical and Industrial EngineeringThe University of IowaIowa CityUSA
  3. 3.IIHR-Hydroscience and EngineeringThe University of IowaIowa CityUSA
  4. 4.Department of RadiologyThe University of IowaIowa CityUSA
  5. 5.Department of Biomedical EngineeringThe University of IowaIowa CityUSA
  6. 6.Department of MedicineThe University of IowaIowa CityUSA
  7. 7.Bioengineering InstituteThe University of AucklandAucklandNew Zealand

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