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Research Papers

Computational Fluid Dynamics Simulations of Particle Deposition in Large-Scale, Multigenerational Lung Models

[+] Author and Article Information
D. Keith Walters

Department of Mechanical Engineering, CAVS SimCenter, Mississippi State University, P.O. Box ME, Mississippi State, MS 39762walters@me.msstate.edu

William H. Luke

Department of Mechanical Engineering, CAVS SimCenter, Mississippi State University, P.O. Box ME, Mississippi State, MS 39762whl30@msstate.edu

J Biomech Eng 133(1), 011003 (Dec 22, 2010) (8 pages) doi:10.1115/1.4002936 History: Received July 13, 2010; Revised October 14, 2010; Posted November 02, 2010; Published December 22, 2010; Online December 22, 2010

Computational fluid dynamics (CFD) has emerged as a useful tool for the prediction of airflow and particle transport within the human lung airway. Several published studies have demonstrated the use of Eulerian finite-volume CFD simulations coupled with Lagrangian particle tracking methods to determine local and regional particle deposition rates in small subsections of the bronchopulmonary tree. However, the simulation of particle transport and deposition in large-scale models encompassing more than a few generations is less common, due in part to the sheer size and complexity of the human lung airway. Highly resolved, fully coupled flowfield solution and particle tracking in the entire lung, for example, is currently an intractable problem and will remain so for the foreseeable future. This paper adopts a previously reported methodology for simulating large-scale regions of the lung airway (Walters, D. K., and Luke, W. H., 2010, “A Method for Three-Dimensional Navier–Stokes Simulations of Large-Scale Regions of the Human Lung Airway  ,” ASME J. Fluids Eng., 132(5), p. 051101), which was shown to produce results similar to fully resolved geometries using approximate, reduced geometry models. The methodology is extended here to particle transport and deposition simulations. Lagrangian particle tracking simulations are performed in combination with Eulerian simulations of the airflow in an idealized representation of the human lung airway tree. Results using the reduced models are compared with those using the fully resolved models for an eight-generation region of the conducting zone. The agreement between fully resolved and reduced geometry simulations indicates that the new method can provide an accurate alternative for large-scale CFD simulations while potentially reducing the computational cost of these simulations by several orders of magnitude.

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Figures

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Figure 1

(a) Eight-generation model of the bronchial region based on the Weibel (19) lung morphology, (b) comprised of successive parent-daughter branching units

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Figure 2

Flow path ensemble models obtained by truncating the eight-generation airway tree shown in Fig. 1: (a) 4-path ensemble and (b) 16-path ensemble

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Figure 3

Example of the stochastic coupling method for unresolved boundary conditions. The resolved pressure at location A is mapped to the unresolved outlet location B, C is mapped to D, etc.

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Figure 4

Static pressure contours on the airway wall (red=high pressure and blue=low pressure) comparing results with (a) the fully resolved geometry and (b) the 4-path ensemble model

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Figure 5

Predicted generational deposition fraction for the coarse grid simulations, fully resolved geometry

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Figure 6

Generational deposition fractions for the coarse grid simulations: (a) 5 μm particles, (b) 10 μm particles, (c) 15 μm particles, and (d) 20 μm particles

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Figure 7

Predicted generational deposition fraction for the fine grid simulations, fully resolved geometry

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Figure 8

Generational deposition fractions for the fine grid simulations: (a) 5 μm particles, (b) 10 μm particles, (c) 15 μm particles, and (d) 20 μm particles

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Figure 9

Generational deposition fractions for (a) 5 μm and (b) 20 μm, comparing results from the 4-path ensemble, using two different boundary condition coupling patterns

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