Comparative Analysis of the Flow in a Realistic Human Airway

TL;DR

The paper tackles the challenge of accurately predicting airway flow by performing fully resolved DNS of inhalation through a realistic airway from a nasal mask to the 6th bronchial bifurcation, at $Re_p=400$ and $Re_p=1200$, validated against high-resolution PIV and 3D-PTV data. It uses a lattice-Boltzmann solver within the m-AIA framework on an ultra-fine unstructured octree mesh, enabling turbulence-free simulations that resolve jets, secondary vortices, and shear-layer instabilities across four anatomical regions. A key contribution is the region-wise analysis of pressure loss and flow instabilities, showing that the nasal cavity dominates total loss at both flow rates but that higher $Re_p$ drives vortex breakdown and enhanced mixing in the naso- and oropharynx, with the carinal bifurcation mitigating upstream unsteadiness. The results provide a high-fidelity benchmark for patient-specific airway modeling and have implications for inhalation therapy design and surgical planning, offering a physical basis for linking geometry, flow rate, vortex dynamics, and transport in the respiratory system.

Abstract

Accurate simulations of the flow in the human airway are essential for advancing diagnostic methods. Many existing computational studies rely on simplified geometries or turbulence models, limiting their simulation's ability to resolve flow features such shear-layer instabilities or secondary vortices. In this study, direct numerical simulations were performed for inspiratory flow through a detailed airway model which covers the nasal mask region to the 6th bronchial bifurcation. Simulations were conducted at two physiologically relevant \textsc{Reynolds} numbers with respect to the pharyngeal diameter, i.e., at Re_p=400 (resting) and Re_p=1200 (elevated breathing). These values characterize resting and moderately elevated breathing conditions. A lattice-Boltzmann method was employed to directly simulate the flow, i.e., no turbulence model was used. The flow field was examined across four anatomical regions: 1) the nasal cavity, 2) the naso- and oropharynx, 3) the laryngopharynx and larynx, and 4) the trachea and carinal bifurcation. The total pressure loss increased from 9.76 Pa at Re_p=400 to 41.93 Pa at Re_p=1200. The nasal cavity accounted for the majority of this loss for both Reynolds numbers, though its relative contribution decreased from 81.3% at Re_p=400 to 73.4% at Re_p=1200. At Re_p=1200, secondary vortices in the nasopharyngeal bend and turbulent shear-layers in the glottis jet enhanced the local pressure losses. In contrast, the carinal bifurcation mitigated upstream unsteadiness and stabilized the flow. A key outcome is the spatial correlation between the pressure loss and the onset of flow instabilities across the four regions. This yields a novel perspective on how the flow resistance and vortex dynamics vary with geometric changes and flow rate.

Figures (18)

• Figure 1: 3D model of the human airway Farkas2020Lizal2020.
• Figure 2: Computational domain.
• Figure 3: Sketch of the experimental setup for PIV and 3D-PTV measurements.
• Figure 4: Equidistant cross sections of the normalized velocity magnitude $u_{mag}/U_p$ at two Reynolds numbers in the $x$-$z$-plane ranging from $y/d_p=4$ to $y/d_p=6.4$, which is highlighted by the black area in the 3D model on the left in Fig. \ref{['fig:slices_re_1200']}. Results for various mesh resolutions are compared to excerpts of the 3D-PTV measurement series described in JohanningMeiners.2024.
• Figure 5: Contours of the normalized velocity magnitude $u_{mag}/U_p^I$ at $Re_p=400$ in the bifurcation (dashed red square and dashed red line for $z=0$ in the sketch). Results for the coarse, medium, and fine meshes are compared to PIV measurements JohanningMeiners.2023.