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Research Papers

Convective Dispersion During Steady Flow in the Conducting Airways of the Human Lung

[+] Author and Article Information
Frank E. Fresconi

Department of Mechanical Engineering, University of Delaware, Newark, DE 19716fresconi@udel.edu

Ajay K. Prasad

Department of Mechanical Engineering, University of Delaware, Newark, DE 19716prasad@udel.edu

J Biomech Eng 130(1), 011015 (Feb 20, 2008) (9 pages) doi:10.1115/1.2838042 History: Received March 05, 2007; Revised June 11, 2007; Published February 20, 2008

The adverse health effects of inhaled particulate matter from the environment depend on its dispersion, transport, and deposition in the human airways. Similarly, precise targeting of deposition sites by pulmonary drug delivery systems also relies on characterizing the dispersion and transport of therapeutic aerosols in the respiratory tract. A variety of mechanisms may contribute to convective dispersion in the lung; simple axial streaming, augmented dispersion, and steady streaming are investigated in this effort. Flow visualization of a bolus during inhalation and exhalation, and dispersion measurements were conducted during steady flow in a three-generational, anatomically accurate in vitro model of the conducting airways to support this goal. Control variables included Reynolds number, flow direction, generation, and branch. Experiments illustrate transport patterns in the lumen cross section and map their relation to dispersion metrics. These results indicate that simple axial streaming, rather than augmented dispersion, is the dominant steady convective dispersion mechanism in symmetric Weibel generations 7–13 during normal respiration. Experimental evidence supports the branching nature of the airways as a possible contributor to steady streaming in the lung.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

Bifurcation geometry and dimensions for the largest bifurcation unit

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Figure 2

Schematic of the three-generational model geometry with nomenclature

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Figure 3

Experimental setup

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Figure 4

Typical normalized mean concentration as a function of nondimensional time from experiments. Circles represent data from multiple trials. The curve gives the average of all trails, along with associated uncertainty bands at 95% confidence level.

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Figure 5

Flow visualization in the cross section at various generation and branch locations for inspiration at Re=10

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Figure 6

Flow visualization in the cross section at various generation and branch locations for inspiration at Re=100

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Figure 7

Flow visualization in the cross section at various generation and branch locations for expiration at Re=10

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Figure 8

Flow visualization in the cross section at various generation and branch locations for expiration at Re=100

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Figure 9

Nondimensionalized effective axial diffusivity for all experiments; error bars represent intervals for 95% confidence level

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Figure 10

Nondimensionalized effective axial diffusivity for generation parameter; error bars represent intervals for 95% confidence level

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Figure 11

Nondimensionalized effective axial diffusivity for direction parameter; error bars represent intervals for 95% confidence level

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Figure 12

Nondimensionalized effective axial diffusivity for Re parameter; error bars represent intervals for 95% confidence level

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