CFD simulation and experimental validation of fluid flow and particle transport in a model of alveolated airways
Introduction
Numerous experimental (Darquenne & Prisk, 2004; Darquenne, West, & Prisk (1998), Darquenne, West, & Prisk (1999); Heyder, 2004; Heyder, Armbruster, Gebhart, Grein, & Stahlhofen, 1975; Heyder, Gebhart, Rudolf, Schiller, & Stahlhofen, 1986; Stahlhofen, Gebhart, & Heyder, 1980) and modeling (Asgharian, Price, & Hofmann, 2006; Darquenne, 2001; Darquenne and Paiva, 1994; Darquenne and Paiva, 1996; Fleming, Conway, Holgate, Bailey, & Martonen, 2000; Harrington, Prisk, & Darquenne, 2006; Yeh and Schum, 1980) investigations have been performed in the past decades to estimate the deposition of inhaled aerosols in the human respiratory tract. While current in vivo experimental techniques can only reliably provide total or regional deposition data, numerical simulations can often provide much more detailed information in both space and time. Computational fluid dynamics (CFD) simulation is a powerful and often indispensible tool for modeling airflow and aerosol transport in realistic and complicated airway geometry. However, one of the most important aspects of this type of simulations is that the methods and results need to be validated before such predictions can be relied on.
There were several validation studies in which numerically computed airflow in the human upper and large airways were compared with experimental measurements. To validate CFD simulations of air flow in a rigid-walled tracheobronchial airway model from trachea up to generation seven, de Rochefort et al. (2007) performed in vitro validation studies by using hyperpolarized 3He magnetic resonance phase-contrast velocimetry. Good agreement between computed and measured velocity profiles at selected cross sections was observed. Some CFD-based predictions of particle deposition profiles in the upper and large airways have also been qualitatively validated by comparing regional deposition statistics (Oldham, Phalen, & Heistracher, 2000), or local maps of deposition (Zhang, Kleinstreuer, & Kim, 2002). Quantitative validation of local deposition patterns has however been scarce. In a recent study by Longest and Vinchurkar (2007) the CFD predicted deposition results for 10 μm particles in a model of three successive airway generations (3–5) were compared to in vitro data (Oldham et al., 2000) and good agreement was obtained.
There have also been some experimental validation studies of air flow in the human peripheral airways. Tsuda, Henry, and Butler (1995) numerically simulated air flow in an axisymmetric model of the pulmonary acinus under rhythmical expansion and contraction. This numerical study was later validated experimentally (Tippe and Tsuda, 1999) in a large-scaled in vitro model using particle image velocimetry (PIV). Qualitative agreements on the flow field were found between CFD predictions and experimental data. Both the simulations and experiments revealed highly complex flow structures in compliant alveolar structures even at very low Reynolds numbers. Karl, Henry, and Tsuda (2004) studied the low Reynolds number flow in a large scale axisymmetric rigid-walled model of a single alveolated duct. The PIV-measured and CFD-simulated flow features qualitatively agreed with each other. This study showed the influence of model geometrical factors (e.g. alveolar cavity aspect ratio) on overall flow features in the periphery of the lung. More recently van Ertbruggen, Corieri, Theunissen, Riethmuller, and Darquenne (2008) reported quantitative comparison of CFD simulations and experimental PIV results for fluid flow in a rigid-walled scaled-up model of an alveolated bend. At seven selected cross sections the velocity profiles were compared and good agreement was found. However, the model geometry was limited to one bend and did not include any bifurcations.
To the authors’ knowledge, there have been no previous published studies which seek to validate simulated individual particle trajectory in the context of respiratory aerosol transport. In this study, a scaled-up model of human alveolated airways was built. The model included three generations and two bifurcations and contained some essential geometrical features of the pulmonary airways. Experimental measurements of fluid flow and particle transport were obtained by PIV and particle tracking velocimetry (PTV), respectively. These experimental data were compared to CFD predictions under identical conditions. This study provides the first direct quantitative validation of numerical studies of airway flow and individual particle trajectory in three-dimensional bifurcated and alveolated airways.
Section snippets
Experimental methods
An in vitro scaled-up model of three generations of alveolated airways of the human lung was constructed (Fig. 1) at the von Karman Institute (VKI) using the same casting techniques as used in a previous study (van Ertbruggen et al., 2008). The cast was made of silicone whose refractive index (1.43) matches that of the carrier fluid (silicone oil, density=970 kg/m3, dynamic viscosity=1 Pa s). The inner diameter of all five airways was 20 mm, and the diameter of the alveolar rings was 45 mm. These
Flow field
For examining the flow features and for validation purposes, velocity field was checked in the symmetry plane (Fig. 3) and at 12 cross sections (Fig. 4). The flow features observed in both the PIV experiments and the CFD simulations were typical of low-Reynolds number flow, and were consistent with those seen in previous studies (Darquenne & Paiva, 1996; Harrington et al., 2006; Karl et al., 2004; Tsuda, Butler, & Fredberg, 1994). In each generation of the model, the flow became fully developed
Discussion
Validation is an important part of any modeling study. In the case of simulating aerosol particle transport in the alveolated airways, such validation has been scarce in the past. The current study used a scaled-up in vitro model to validate the CFD predictions with PIV and PTV experimental data. While this is still an in vitro model, such data provided some valuable information regarding the accuracy of numerical simulations of fluid flow and particle transport in small airways and of low
Acknowledgment
This work was supported by NIH Grant RO1 ES011177.
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