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Research Papers

# Simulation of Turbulent Airflow Using a CT Based Upper Airway Model of a Racehorse

[+] Author and Article Information
Vineet Rakesh

Department of Biological and Environmental Engineering, Cornell University, 208 Riley Robb Hall, Ithaca, NY 14853vr46@cornell.edu

Ashim K. Datta1

Department of Biological and Environmental Engineering, Cornell University, 208 Riley Robb Hall, Ithaca, NY 14853akd1@cornell.edu

Normand G. Ducharme

Department of Clinical Sciences, Cornell University, C2-528 Vet College, Ithaca, NY 14853ngd1@cornell.edu

Anthony P. Pease

Department of Molecular Biomedical Sciences, North Carolina State University, Box 8401, NCSU Campus, Raleigh, NC 27606tony̱pease@ncsu.edu

1

Corresponding author.

J Biomech Eng 130(3), 031011 (Apr 29, 2008) (13 pages) doi:10.1115/1.2913338 History: Received April 26, 2007; Revised September 03, 2007; Published April 29, 2008

## Abstract

Computational model for airflow through the upper airway of a horse was developed. Previous flow models for human airway do not hold true for horses due to significant differences in anatomy and the high Reynolds number of flow in the equine airway. Moreover, models that simulate the entire respiratory cycle and emphasize on pressures inside the airway in relation to various anatomical diseases are lacking. The geometry of the airway was created by reconstructing images obtained from computed tomography scans of a thoroughbred racehorse. Different geometries for inhalation and exhalation were used for the model based on the difference in the nasopharynx size during the two phases of respiration. The Reynolds averaged Navier–Stokes equations were solved for the isothermal flow with the standard $k-ϵ$ model for turbulence. Transient pressure boundary conditions for the entire breathing cycle were obtained from past experimental studies on live horses. The flow equations were solved in a commercial finite volume solver. The flow rates, computed based on the applied pressure conditions, were compared to experimentally measured flow rates for model validation. Detailed analysis of velocity, pressure, and turbulence characteristics of the flow was done. Velocity magnitudes at various slices during inhalation were found to be higher than corresponding velocity magnitudes during exhalation. The front and middle parts of the nasopharynx were found to have minimum intraluminal pressure in the airway during inhalation. During exhalation, the pressures in the soft palate were higher compared to those in the larynx, epiglottis, and nasopharynx. Turbulent kinetic energy was found to be maximum at the entry to the airway and gradually decreased as the flow moved inside the airway. However, turbulent kinetic energy increased in regions of the airway with abrupt change in area. Based on the analysis of pressure distribution at different sections of the airway, it was concluded that the front part of the nasopharynx requires maximum muscular activity to support it during inhalation. During exhalation, the soft palate is susceptible to displacements due to presence of high pressures. These can serve as critical information for diagnosis and treatment planning of diseases known to affect the soft palate and nasopharynx in horses, and can potentially be useful for human beings.

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## Figures

Figure 1

Anatomy of the airway of a horse compared to that of a human. Computations have been done using the equine airway. The human airway anatomy is shown only for comparison.

Figure 2

Flowchart showing the sequence of steps followed to develop the airflow model for the equine upper airway. The geometry of the model was created in Steps 1–5. The flow equations were subsequently solved in the commercial CFD solver, Fluent. MIMICS , MAGICS , GAMBIT , and TGRID are geometry reconstruction and meshing softwares used for the model.

Figure 3

Postmortem, transverse computed tomographic (CT) image of an equine head centered on the rostral aspect of the larynx. The animal is a 3year old intact male thoroughbred racehorse with the horse in dorsal recumbency. The airways are colored completely white to outline the area and are labeled with arrows. The other structures are related to the soft tissues (gray) and bones (gray to white) of the head.

Figure 4

The surface mesh created in MAGICS including the inflow and outflow surfaces created in GAMBIT after smoothing and improvement of the STL mesh. The STL mesh was generated in MIMICS by reconstruction of CT images, similar to the one shown in Fig. 3. The image has been taken after importing it to TGRID . The mesh has 278,352 triangular elements with maximum equiangle skewness of 0.7. An enlarged view of the region near the larynx is also shown in the figure.

Figure 5

The 3D geometry representing the equine upper airway reconstructed from CT scanned images obtained from a 3year old intact male thoroughbred racehorse. The figure on the top represents the geometry during the inspiratory phase and the one below represents the expiratory phase geometry obtained by increasing the diameter of the nasopharynx in the geometry manipulation software.

Figure 6

Schematic of the computational domain used for the model, which shows the different slices across the airway used in the analysis. The pressure boundary conditions at the nostrils and trachea, and the zero velocity boundary conditions on the wall are also shown in the figure.

Figure 7

Experimentally measured (28) static tracheal pressure history at 30cm from the larynx during the respiratory cycle of an exercising horse (galloping at 14m∕s)

Figure 8

Experimentally measured flow rate from the work of Radcliffe (28) that corresponds to the tracheal pressure history shown in Fig. 7. Superimposed on it is the computed flow rate using the pressure history from Fig. 7 and the geometry obtained in this study.

Figure 9

Computed flow rate history for the left and right nostrils of a horse for a cycle of respiration. The flow rates correspond to tracheal pressure history shown in Fig. 7.

Figure 10

(a) Computed area-averaged static pressure histories at different locations along the airway for the respiratory cycle specified by the pressure history in Fig. 7. (b) Computed area-averaged velocity magnitudes at the locations of the airway for the same respiratory cycle.

Figure 11

Computed pressure contours at the surface of the equine airway at peak inspiratory flow corresponding to a pressure of 4336Pa at the trachea. The time at peak inhalation is 0.165s, as shown in Fig. 7.

Figure 12

Computed path lines of velocity magnitude obtained at inspiratory pressure of 4336Pa at the trachea (at t=0.165s)

Figure 13

Velocity magnitude contours at different slices of the airway at maximum inspiratory pressure of 4336Pa at the trachea (at t=0.165s)

Figure 14

Contours of axial velocity along two longitudinal planes across the airway near the front part of nasopharynx and larynx at maximum inspiratory pressure of 4336Pa at the trachea (at t=0.165s)

Figure 15

Contours of turbulent kinetic energy plotted at peak tracheal inspiratory pressure of 4336Pa. An enlarged view of the region with rapid change in turbulent kinetic energy near the nostrils and the larynx is also shown in the figure (at t=0.165s).

Figure 16

Turbulent kinetic energy plotted as a function of position on the wall of the airway at peak inspiratory pressure of 4336Pa at the trachea (at t=0.165s)

Figure 17

Computed pressure contours at the surface of the equine airway at peak expiratory pressure of 3068Pa at the trachea. The time at peak exhalation is 0.385s, as shown in Fig. 7.

Figure 18

Velocity magnitude contours at different slices of the airway at peak expiratory pressure corresponding to 3068Pa at the trachea (at t=0.385s)

Figure 19

Turbulent kinetic energy plotted against position on the wall of the airway at peak expiratory pressure of 3068Pa at the trachea (at t=0.385s)

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