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Research Papers

Visualizing Flow Partitioning in a Model of the Upper Human Lung Airways

[+] Author and Article Information
K. Bauer, H. Chaves, Ch. Brücker

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

J Biomech Eng 132(3), 031005 (Feb 08, 2010) (9 pages) doi:10.1115/1.4000871 History: Received February 05, 2009; Revised September 28, 2009; Posted December 22, 2009; Published February 08, 2010; Online February 08, 2010

The convective transport of fluid within the human upper airways is investigated in a transparent model of the tracheobronchial tree. Oscillatory flow through the branching network with six generations was studied at varying Reynolds numbers between 400 and 2600 and Womersley numbers from 5.5 to 12.3 in the trachea representing clinical conditions during high frequency oscillatory ventilation. The flow partitioning within the model was visualized using advection of neutrally buoyant tracer particles, which were illuminated by short light pulses and recorded by a high speed camera. Integration of the particle locations for a large number of cycles provides the probability distribution of particles passing certain branches within the bifurcating network, and thus, the dispersion of particles in the airways. The results show the different characteristics of flow partitioning at varying Womersley and Reynolds numbers.

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Copyright © 2010 by American Society of Mechanical Engineers
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Figures

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Figure 1

(a) Positive model of the human bronchial tree; (b) silicone model with hollow branches of the bronchial tree used for flow measurements

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Figure 2

Schematical setup for flow measurements in the lung model at the oscillating flow

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Figure 3

Schematical setup for telecentric image acquisition

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Figure 4

Flow chart for image evaluation; top images represent the originally recorded images

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Figure 5

Relative particle probability distribution exemplarily for α=11.0 and Re=1590, color scale represents probability values in % related to the maximum value of 63

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Figure 6

Contour lines of probability distributions within the human lung for varying Womersley and Reynolds numbers; the contour lines represent 15%, 30% and 50% probability, whereas the maximum penetration depth indicates the lowest probability

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Figure 7

Contour lines of probability distributions within the human lung for different Womersley but constant Reynolds numbers

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Figure 8

Average probability distribution at selected cross sections of each generation for different Womersley numbers at Re=1980; higher probabilities are coded by larger font size

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Figure 9

Probability distribution at selected cross sections of each generation for different Reynolds numbers at α=11

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