Research Papers

The Influence of Airway Tree Geometry and Ventilation Frequency on Airflow Distribution

[+] Author and Article Information
Katrin Bauer

Institute of Mechanics and Fluid Dynamics,
TU Bergakademie Freiberg,
Lampadiusstr. 4,
Freiberg 09599, Germany
e-mail: Katrin.Bauer@imfd.tu-freiberg.de

Christoph Brücker

Institute of Mechanics and Fluid Dynamics,
TU Bergakademie Freiberg,
Lampadiusstr. 4,
Freiberg 09599, Germany

1Corresponding author.

Manuscript received September 30, 2014; final manuscript received April 24, 2015; published online June 9, 2015. Assoc. Editor: Naomi Chesler.

J Biomech Eng 137(8), 081001 (Aug 01, 2015) (10 pages) Paper No: BIO-14-1482; doi: 10.1115/1.4030621 History: Received September 30, 2014; Revised April 24, 2015; Online June 09, 2015

The human lung is known to be asymmetric and heterogeneous which leads to an inhomogeneous distribution of air. Within the scope of this paper the influence of the upper airway tree geometry on ventilation distribution and the differences between conventional mechanical ventilation (CMV) and high frequency oscillatory ventilation (HFOV) will be analyzed. The comparison is carried out under the assumption of positive pressure ventilation. Thereby, the mechanics of lung tissue is expected to play a minor role. Oscillatory flow is therefore generated numerically at a 3D model geometry of the upper human airways. For large enough frequencies in the range of HFOV (here 7 Hz) the shape of the velocity profiles changes, but this had no measurable influence on the flow distribution. The flow division is rather governed by airway tree geometry, i.e., branch length, curvature, and tortuosity. A convective net transport of fresh air to the distal branches occurs due to the relocation of mass during ins-/expiration driven by secondary flow. However, a mixing by secondary flow plays a minor role as was suggested by the visualization of particle pathlines. The phenomenon of steady streaming is further investigated by calculating the mean flow of one breathing cycle. Streaming was found to contribute only to a minor percentage to the overall mass transport in the upper lung airways.

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Fig. 1

Discretized lung geometry, (a) top view, (b) enlarged view of trachea inlet, and (c) enlarged view of a discretized outlet

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Fig. 2

Velocity profiles in selected cross sections of the main bifurcation during ventilation, dashed lines apply for normal ventilation (α = 3), solid lines for HFOV (α = 15)

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Fig. 3

Velocity patterns during peak inspiration in cross section L1, (a) secondary flow structure with in plane velocity magnitude and velocity vectors, α = 3 (top) and α = 15 (bottom) and (b) velocity magnitude in main flow direction

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Fig. 4

(a) Origin of particle pathlines in the second daughter generation presented for two different views at the lung model: left top view and right front view. The colors specify the originating quadrant of the particles, (b) top view the particle pathline distribution for CMV (α = 3) and HFOV (α = 15) during inspiration, and (c) during expiration.

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Fig. 5

Pathline distribution in the right section of the lung model for low and high Womersley number. The pathline source is in the lower right corner at the end of the trachea.

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Fig. 6

Top and front view on the particle distribution during the inspiration phase for CMV, particle distribution is color coded according to injection point at the top of the trachea

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Fig. 7

Mass distribution at certain stages during inspiration at CMV, particles are color coded according to particle injection time step, red-new, blue-old

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Fig. 8

Particle distribution at the end of inspiration for four successive ventilation cycles at HFOV (α = 15), the TV is 1/3 of the model dead space. Particles are again color coded according to their injection point in the trachea.

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Fig. 9

(a) Lung model with marked outlets for further analysis and injected particles color coded according to their lifetime in the model, blue-new, red-old, (b) flow during one ventilation cycle for selected outlets at CMV, and (c) flow during one ventilation cycle for selected outlets at HFOV (α = 15)

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Fig. 10

(a) Peak flow rate as function of the product from tortuosity τ and total branch length at HFOV and (b) peak flow rate as function of the dimensionless time of the ventilation cycle as it occurs during HFOV

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Fig. 11

Structure of streaming flow in the midplane of the main bifurcation. (a) Streaming flow is obtained by integration over five breathing cycles of experimental PIV measurements and (b) CFD results, inflow (red) and outflow (blue) regions are marked by colored arrows.

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Fig. 12

Isocontours of steady streaming flow, red color indicates inflow, blue outflow, cross sections AA–CC with color coded isovelocity lines of net streaming flow, velocity vectors indicate the cross-sectional structure of the secondary flow

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Fig. 13

Vertical streaming velocity presented in selected planes of the main bifurcations, (a) lung model depicting the plane location, (b) vertical velocity compared for similar Reynolds number but low and high Womersley number, and (c) vertical velocity compared for similar Womersley number but low and high Reynolds number



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