Validating CFD predictions of highly localized aerosol deposition in airway models: In vitro data and effects of surface properties

Author’s Accepted Manuscript

Validating CFD Predictions of Highly Localized Aerosol Deposition in Airway Models: In Vitro Data and Effects of Surface Properties Landon T. Holbrook, P. Worth Longest

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S0021-8502(13)00025-6 http://dx.doi.org/10.1016/j.jaerosci.2013.01.008 AS4632

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9 November 2012 14 January 2013 14 January 2013

Cite this article as: Landon T. Holbrook and P. Worth Longest, Validating CFD Predictions of Highly Localized Aerosol Deposition in Airway Models: In Vitro Data and Effects of Surface Properties, Journal of Aerosol Science, http://dx.doi.org/10.1016/ j.jaerosci.2013.01.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Validating CFD Predictions of Highly Localized Aerosol Deposition in Airway Models: In Vitro Data and Effects of Surface Properties Landon T. Holbrook1 and P. Worth Longest1,2* 1

Department of Mechanical and Nuclear Engineering Virginia Commonwealth University, Richmond, VA 2

Department of Pharmaceutics Virginia Commonwealth University, Richmond, VA Running title: Validating CFD Predictions of Localized Aerosol Deposition Submitted to: Journal of Aerosol Science Dr. P. Worth Longest, PhD (*Corresponding author) Virginia Commonwealth University 401 West Main Street P.O. Box 843015 Richmond, VA 23284-3015 Phone: (804)-827-7023 Fax: (804)-827-7030 Email: [email protected]

Keywords: Airway particle deposition, microdosimetry, surface roughness, surface coating, respiratory drug delivery, modeling airway deposition, in vitro aerosol deposition, asymmetrical airway bifurcations

ABSTRACT Local deposition of pharmaceutical and environmental aerosols governs desorption, uptake, and biological response within the respiratory airways. Few studies have reported estimates of numerical microdosimetry and even fewer have compared these results with experiments. This

study evaluated the effects of surface coating and roughness on the local deposition of inhaled coarse micrometer particles in an in vitro asymmetric double bifurcation geometry. The double bifurcation geometry is representative of airway generations 3-5 and includes mean asymmetry approximations from previous anatomical studies. Polystyrene latex 10 μm monodisperse particles were delivered at a steady state tracheal flow rate of 60 liters per minute (LPM) and mean local deposition patterns were resolved on a grid of 0.75 mm squares using fluorescent microscopy. The three airway geometry surfaces tested were unaltered, coated with silicone oil, and sanded-coated. For the hard plastic in vitro models employed, coating the surface was shown to be important in order to prevent bounce and re-entrainment of the particles. Sanding the models altered the local deposition profile in an uncontrolled way and is therefore not recommended for future experiments. The best overall match between the in vitro results and CFD simulations was the coated experimental geometry and coarse wall roughness simulations. For this case, the relative error between the experiments and simulations for total deposition was 6%. On a local deposition basis, cumulative lines of deposition fraction in the x and y-directions showed reasonable agreement between the experiments and simulations. However, some evidence of post-deposition particle rolling or spreading was observed with the coated experiments at the second bifurcation. Comparing experimental and CFD results cell by cell, higher maximum deposition enhancement factors (DEFs) were observed for the in vitro cases, perhaps due to factors not included in the CFD simulations. This result implies that previously predicted maximum DEF values from CFD simulations may be conservatively low and that actual values with in vitro models or in vivo may be even higher than predicted. In conclusion, this study provides a valuable new dataset for understanding the effects of surface characteristics

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on local deposition, assessing hotspot magnitude in the tracheobronchial airways, and validating CFD predictions.

1. Introduction Total and regional airway depositions of aerosols are often predicted with numerical models (Asgharian et al., 2001; Finlay and Martin 2008; ICRP 1994; Martonen 1982; NCRP 1997), and these estimates are used to assess the dose and potential health effects of both inhaled pollutants and inhaled medicines. Total deposition refers to conditions throughout the respiratory tract, whereas regional deposition typically includes broad segments ranging from the tracheobronchial or pulmonary sections down to the branch-averaged level. In contrast with these broad assessments, hotspots of aerosol deposition are known to form resulting in highly localized areas of dose with values many times greater than total or regional approximations (Balashazy et al., 2003; Bell and Friedlander 1973; Longest et al., 2006; Martonen 1986; Phalen et al., 2006; Xi and Longest 2008; Zhang et al., 2005). Deposition enhancement factors (DEFs), defined as the ratio of local to regional dose within an airway segment, have been predicted in the range of 10 to 103 for microparticles (Balashazy et al., 1999; Longest et al., 2006; Xi et al., 2008; Zhang et al., 2005) and 10 to 102 for nanoparticles (Balashazy and Hofmann 2000; Longest and Xi 2007; Xi and Longest 2008; Zhang et al., 2005). Formation of these hotspots is significant, because they represent areas within which a majority of the dose potentially interacts with the respiratory epithelium and may be absorbed into the bloodstream. For pharmaceutical aerosols, the formation of concentrated deposition hotspots affects dissolution of soluble drug particles, targeting of topical receptors, and ultimately the bioavailability and effectiveness of the drug for either lung or systemic applications (Longest and Holbrook 2012). Considering inhaled pollutants, the concentration of dose in localized areas increases the likelihood for cellular 3

damage or adverse reactions and may increase blood absorption (Balashazy et al., 2003; Phalen et al., 2006). As a result, it is important to accurately resolve both the regional and highly localized deposition characteristics of inhaled aerosols. Computational fluid dynamics (CFD) simulations provide an excellent method to predict regional and highly localized deposition characteristics in the respiratory airways. Applications of CFD to predict airway deposition for both ambient and pharmaceutical aerosols were recently reviewed by Kleinstreuer et al. (2008) and Longest and Holbrook (2012). As CFD, imaging, and computational resources have increased over time, the recent trends in airway deposition simulations have been towards (i) larger and more complete respiratory geometries (Kleinstreuer and Zhang 2009; Longest et al., 2012a; Tian et al., 2011b; Walters and Luke 2011), (ii) improved turbulence modeling (Farkas and Balashazy 2008; Jayaraju et al., 2008; Lambert et al., 2011), (iii) including the additional complexities of pharmaceutical aerosols (Farkas et al., 2006; Longest and Hindle 2009a; Longest et al., 2008; Longest et al., 2012b; Shi and Kleinstreuer 2007; Tian et al., 2011a; Tian et al., 2011b), and (iv) predicting highly localized deposition (Longest and Holbrook 2012; Xi and Longest 2008; Zhang and Kleinstreuer 2011). Computational fluid dynamics simulations typically present local deposition concentrations based on the DEF, calculated for individual control volume surfaces or within an area with a characteristic dimension of 150 - 1000 μm, which corresponds to approximately 15 - 100 epithelial cells (Balashazy et al., 2003; Xi and Longest 2007; Xi and Longest 2008; Zhang et al., 2005). Longest et al. (2006) proposed a microdosimetry factor , which makes calculation of local cell dose more direct, and was based on a constant sample area. However, the sampling areas implemented for DEF or  in all of these studies are somewhat arbitrary. As described previously by Oldham (2006), Longest and Vinchurkar (2007b), and Longest and Oldham

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(2008), CFD studies often validate model performance by comparing with in vitro deposition data for an entire region of the airways. For example, Xi et al. (2008) compared deposition data in the upper tracheobronchial region with the in vitro experimental deposition results of Cohen et al. (1990) and Gurman et al. (1984) across a range of nanometer to micrometer particle sizes for the same patient-specific geometry. Robinson et al. (2006) compared the total deposition of submicrometer particles between CFD model predictions and in vitro results in a segment of the mid-tracheobronchial airways. Kleinstreuer and Zhang (2009) compared CFD predictions of total tracheobronchial deposition with in vivo results from a variety of studies. Other recent CFD studies have compared deposition in the upper TB airways with in vitro data on a branchaveraged basis (Inthavong et al., 2010; Lambert et al., 2011; Ma and Lutchen 2009; Tian et al., 2011a; Xi and Longest 2008). However, very few studies have validated CFD results with highly localized in vitro data that approaches the scale of the DEF and  predictions. This raises concerns about the quality of CFD-predicted highly localized dose values in airway models. In general, there is currently a lack of in vitro data in airway models that can be used to validate highly localized CFD predictions. To implement an in vitro dataset for localized validation, it should (i) be of a similar resolution compared with the localized CFD predictions, (ii) provide a good description of the experimental operating conditions, (iii) provide information about the inlet geometry and inlet particle profile, and (iv) fully describe or provide the geometric model. Studies reporting highly localized (~ 1 mm resolution) deposition data include Schlesinger et al. (1982), Oldham et al. (2000), Oldham (2006), and Longest and Oldham (2008). The study of Schlesinger et al. (1982) does not implement an available geometry. Longest and Oldham (2008) considered the regional and local depositions of submicrometer particles. Therefore, only two studies currently exist which are conducive to the validation of highly

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localized micrometer particle deposition in the airways. Computational fluid dynamics studies reporting qualitative comparisons with highly localized experimental datasets include Zhang et al. (2002), Longest and Oldham (2006), and Isaacs et al. (2006). For micrometer particles aerosols, only the studies of Oldham et al. (2006; 2000), Longest and Vinchurkar (2007a; 2007b), and Vinchurkar and Longest (2008) have quantitatively compared CFD results with highly localized aerosol deposition data. However, it is noted that all of these localized quantitative comparison studies were conducted in the same double bifurcation airway model, which was symmetric about two planes. Clearly, improved use of existing and new welldocumented datasets of localized deposition in airway models are needed to improve the validation of localized CFD results. One issue with determining the quality of a CFD solution is establishing the meaning of numerical model validation. Oldham (2006) discussed how the definition of validation can range from indicating that a code executes without error to defining a range of problems for which predictions are satisfactory. Validation of CFD results compared with in vitro data is defined in this study as determining the degree to which simulation predictions match benchmark experiments for specific output parameters over a specified range of physical conditions. Output parameters may include pressure drop, velocity fields, or regional and highly localized deposition characteristics. As illustrated by Longest and Vinchurkar (2007a), agreement between CFD and in vitro predictions of total deposition does not imply agreement in the local deposition patterns. Other instances of similar total deposition and different local deposition patterns were reported by Longest and Oldham (2006). Furthermore, agreement in deposition between numerical and experimental results does not imply that all details of the flow fields match. Instead, agreement in deposition can only be interpreted to imply that the flow field is

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sufficiently resolved to match the in vitro deposition data at the scale considered. Validation for a specific range of physical conditions indicates that the numerical model is accurate provided the physics controlling the output parameter(s) of interest do not change. For example, a validation for deposition with laminar flow and impaction does not imply that the numerical model is accurate for turbulent flow and diffusion. Finally, it is noted that numerical model validation with in vitro data only implies that the physics of the experimental system have been captured with respect to the parameter(s) of interest, not that the in vitro system is consistent with in vivo conditions. Two factors potentially affecting both the regional and local aerosol deposition in respiratory airway in vitro models are the surface roughness and surface coating. Oldham (2006) presented images of particles depositing on surface roughness ridges in double bifurcation models and indicated that roughness characteristics may play a role in both local and total deposition. Kelly et al. (2004a) considered replicas of the nasal cavity using two rapid prototyper techniques with build layer thicknesses of approximately 0.1 mm and 0.05 mm. In vitro experiments indicated more deposition in the coarse prototyped geometry for micrometer particles (Kelly et al., 2004a); however, deposition was similar between the coarse and fine in vitro models for nanoaerosols (Kelly et al., 2004b). As a result, the Kelly et al. (2004a; 2004b) data indicates that surface roughness of the nasal geometry increases deposition due to impaction. Shi et al. (2007) improved agreement between CFD model predictions of nasal particle deposition and the Kelly et al. (2004a) data by defining a near-wall particle capture region for particles greater than 4 μm to better approximate wall roughness effects in the nasal cavity. Schroeter et al. (2011) considered both the smoothness and surface roughness of the geometry used by Kelly et al. (2004a; 2004b). This study showed that smoothing the Kelly et al.

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in vitro nasal model significantly reduced deposition and that the effects of surface roughness on deposition could be captured using a Stokes number parameter that had a diameter proportional to the pressure drop in the geometry (Garcia et al., 2009). Considering coatings of in vitro deposition models, the previous studies of Oldham et al. (2006; 2000) and Longest and Oldham (2006; 2008) implemented a flexible silicone to build the hollow airway models and did not implement a surface coating. However, impactor studies of aerosol size and other studies of aerosol deposition frequently coat surfaces on which particles deposit to prevent bounce, rolling, and resuspension (Delvadia et al., 2010; Kamiya et al., 2004; Tian et al., 2011b). Understanding the effects of both surface roughness and coating on total and local deposition are critical for better comparisons between in vitro results and CFD predictions of total and highly localized deposition. The objective of this study is to provide regional and highly localized deposition data in a well defined bifurcating airway geometry with various surface properties for the validation of CFD predictions. The airway geometry selected is an asymmetric double bifurcation model of respiratory generations G3-G5 that has not been previously considered and is based on well defined physiologically realistic bifurcation (PRB) units specified originally by Heistracher and Hofmann (1995). In vitro experiments are implemented to generate and deposit a monodisperse aerosol of 10 μm particles in the double bifurcation model at a tracheal flow rate of 60 LPM. Regional and highly localized deposition characteristics are determined by counting the deposited particles with a florescent microscope on a grid with a surface resolution of 0.75 mm x 0.75 mm. The in vitro geometries are produced using rapid prototyping and surface properties are varied by considering an unaltered case, a coated case, and a sanded and coated case. The cross-sectional particle profile entering the geometry is also quantified in separate experiments

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based on deposition on an inlet sampling grid. CFD simulations of smooth and rough walled conditions are then used to predict deposition and compared with the in vitro data using multiple approaches. Results of this study provide new highly localized data for validating CFD predictions, insights into the effects of surface roughness and coating on total and local deposition when using in vitro geometries, and a framework for conducting future validation studies of highly localized CFD deposition predictions.

2. Methods 2.1. Airway Geometries The geometry chosen to examine highly localized deposition is a double bifurcating representation of generations G3-G5 of the tracheobronchial airways (Figure 1a). An in-house program based on the PRB equations of Heistracher and Hofmann (1995) and modified by Hegedus et al. (2004) was used to produce single bifurcating units as specified by eleven geometric parameters and two sigmoid functions. Appropriate values of these variables were determined based on previous measurement studies (Horsfield et al., 1971; Yeh and Schum 1980) and correlations given by Koblinger and Hofmann (1985) and Phalen (1978). To construct an asymmetric model, the daughter-to-daughter asymmetry ratio was set as 1.17, which represents a mean asymmetry value based on the study by Koblinger and Hofmann (1985). The asymmetric model used a daughter-to-parent ratio of 0.8 based on the study of Thompson (1942) and more recently the daughter-to-parent ratios from previous experimental studies of the airways (Oldham et al., 2000). The daughter diameters were determined by first establishing a mean value from the daughter-to-parent ratio and then adjusting the diameters to comply with the daughter-to-daughter asymmetry ratio. This process led to the diameters shown in Table 1.

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Airway lengths were calculated based on the diameter of each segment and the length to diameter ratio (L/D) reported by Phalen et al. (1978), which are both reported in Table 1. The airway measurement convention implemented by Phalen et al. (1978) was also adopted in this study where the length was based on the distance between intersections of airway centerlines. These intersections and the associated airway lengths used in this study are illustrated as dots and solid lines, respectively, in Figure 1. The dashed lines in Figure 1 illustrate the start and end of the first PRB unit and the outlets of the remaining two PRB units. Additional lengths of airway were positioned between the PRB units and at the inlet and outlets to match the anatomical centerline length data. The branching curvature ratio is defined as the radius of circular curvature of the branch extending from the parent divided by the diameter of the daughter branch. Similarly, the carinal curvature ratio is defined as the curvature radius in the center of the bifurcation divided by the diameter of the daughter branch. The branch angle was measured with respect to the central axis of the parent, just as Heistracher and Hofmann (1995) defined it. Additionally, the sum of the asymmetric angles was held constant at 70 degrees with the major daughter having an angle of 15 degrees and the minor daughter having an angle of 55 degrees. The geometrically defined in vitro model was constructed using a Viper SLA Rapid Prototyper with Accura 60 resin (3D Systems, Valencia, CA). This machine builds layers in the xy-plane with a thickness of 0.1 mm. These layers were built upward in the z-direction shown in Figure 1. This orientation minimized the structural supports that were required, which must be cleaned before use. Supports were removed after construction by scraping and applying an isopropyl alcohol wash. As shown in Figure 1b, the geometric models were built in two halves that were symmetric about the z-axis. The model halves were held in place during the

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experiment with small bolts positioned primarily at the carinal ridges and sealed with the coating material (heavy-duty silicone, MSP Corporation, Shoreview, MN) to make the model airtight. In vitro models were finished to produce three cases, which were unaltered, coated, or sanded and coated. For all models, the supports were removed, the alcohol wash was applied, and the model was dried in an ultra-violet dryer. The unaltered model had no further modifications. The coated model was coated with silicone oil (heavy-duty silicone, MSP Corporation, Shoreview, MN) by plugging the ends and filling the model with liquid silicone oil and allowing it to sit overnight before draining the next day. The silicone oil that was used had a density and viscosity of 980 kg/m3 and 58.8 Pa-s, respectively. The sanded-coated model underwent the same coating, but before it was coated it was sanded in sections for two minutes per section using a microfine P1500 to P1200 grit Norton sanding sponge (Saint-Gobain Abrasives, Inc., Stephenville, TX). Redistribution of the silicone oil during the experiments was minimized by implementing a thin coating and employing the shortest run times possible while still providing sufficient particle numbers to quantify local deposition. The surface preparation techniques were evaluated at the first bifurcation using a surface profilometer (Ambios XP-1, Ambios Technology, Santa Cruz, CA) to determine the surface profile and calculate the roughness of each model. Roughness was characterized using a rootmean-squared convention in which Rq

1 n 2 ¦ zi . In this expression, zi is the height of the n i1

profile at a given distance and n is the number of sampled points (n  4800).

2.2. Experimental Methods Independent experiments were performed to determine the inlet particle profile and particle deposition within the airway models. As illustrated in Figure 2, compressed air was 11

filtered, dried, and cooled in a Speedaire Dryer (Dayton Parts, Harrisburg, PA), at a regulated pressure of 20 PSI (137.9 kPa). A modified Lovelace-type compressed air nebulizer (In-Tox Products, Albuquerque, NM) was used to generate an aerosol using 10 μm monodisperse 1% solution polystyrene latex (PSL) particles (Duke Scientific, Palo Alto, CA). The particles had a reported geometric diameter of 10.1 μm with a reported density of 1.05 g/cm3 resulting in an aerodynamic diameter of 10.3 μm. The PSL solution was diluted 15 to 1 according to Raabe (1968) to ensure less than 10% doublet particle generation. This nebulizer was operated at 20 PSI (137.9 kPa) and produced a flow rate of 1.34 LPM. The aerosol was radially diluted with cool and dry air, again from the Speedaire Dryer, using a 10:1 ratio. The diluted and dried aerosol was then electrostatically discharged using an Aerosol Neutralizer (3054A, TSI, Minneapolis, MN) and excess aerosol was routed to a HEPA filter to provide the correct flow rate to the in vitro model. The primary aerosol stream was introduced to the model through the conical nozzle shown in Figure 1b. A downstream vacuum pump pulled 7.5 LPM of air through the model outlets with 5 μm polycarbonate filters (Cyclopore membrane 7060-2513; Whatman Inc., Florham Park, NJ) attached to each outlet branch. This flow rate at G3 is consistent with a tracheal flow rate of 60 LPM, which represents an adult breathing during medium activity conditions. The bifurcation model was attached to the outlet of the conical nozzle with gravity oriented in the negative z-direction based on the axes shown in Figures 1 and 2. That is, gravity acted perpendicular to the single plane of symmetry in the geometry. Prior to the experiments, the system was leak tested by applying a static pressure of approximately 6 kPa. The system was found to maintain approximately 80% of this pressure over a time period of 2 minutes. To assess deposition, the prepared in vitro models were individually connected to the system with flow and the particles were allowed to deposit on their

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surfaces. The unaltered model was run for 4 minutes and the coated models were both run for 1 minute. Once the deposition phase was complete, the geometry was removed from the system and each half was labeled and placed in a petri dish until it could be counted. Counting was done on a Carl Zeiss Axio A1 Inverted microscope (Carl Zeiss Microscopy, LLC, Thornwood, NY) with a 10x eyepiece and a 10x objective using an 26 mm glass reticle with etched grid dimensions 15 x 15 mm. This setup was calibrated and the reticle was found to show 1.5 x 1.5 mm primary grid cells at 100x magnification and 4 equal squares inside each primary grid cell. Particles were visually identified and totaled in the 0.75 mm squares. The geometry was built in two halves, top and bottom, so it could be disassembled and each half could be resolved independently (Figure 1b). Custom arms were constructed and attached to the microscope stage to allow counting of the inverted geometry while suspending it over the objective. The stage was equipped with a platform that was manipulated by two dials. These dials adjusted the x-position and y-position independently (coordinates shown in Figure 1a). The dials were equipped with metric scales which allowed for the view to be adjusted by a measured amount. Movement through the geometry by these measured amounts was confirmed by visual inspection and ensuring that the “left edge” of a current view was the same as the “right edge” on the previous view. The focus was then adjusted throughout the z-axis (Figure 1) to resolve each particle and ensure that only particles in focus were counted, such that each particle was only counted once. Due to the amount of time required to count the local deposition fields, only one experiment was conducted for each of the three in vitro surface property cases. The total number of particles passing through the model was determined by counting and sampling the deposition on tubing, filter holders, and filters. The filters were counted directly by inspection with the fluorescent microscope. Filter holders and sections of tubing were rinsed,

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shaken, and sonicated in an appropriate volume of distilled water to remove the particles from the surface. The concentration of particles was determined by counting the number of particles using a Neubauer Hemacytometer. Multiplying this concentration by the volume of wash fluid provided the total number of particles removed. This process was repeated until the concentration decreased by three orders of magnitude. Particle profiles entering the geometry were determined experimentally using a crosssectional insert and applying the particle counting procedure described above in separate experiments. The inlet particle profile was determined by counting the number of particles that deposited on an insert designed to sample the flow after the neutralizer and before the geometry inlet. This insert is illustrated in Figure 3a and had horizontal bars 0.25 mm in width and 0.4 mm in depth. The sampling area of the insert was only 35% of the circle area, which allowed flow to continue around the insert without largely altering the inlet particle distribution, as shown in Figure 3a. To determine the inlet particle distribution, the system was run at 7.5 LPM and the particles depositing on the horizontal bars of the insert were counted using fluorescent microscopy in 0.75 mm squares, just as with the counting of the airway model. Each horizontal bar of the insert represented a row of information and the microscope reticule was used to distinguish the columns. This approach of sampling is thought to capture the particle distribution well because the large particles will likely deposit on the flat surfaces of the insert. This method of determining the inlet particle distribution will need to be revised when the primary mode of deposition is not impaction. Total deposition fractions (DFs) were calculated as the number of particles deposited in the model divided by the number of particles entering the model. The number of particles entering the model was taken as the sum of deposited particles in the model, exit tubing, filter holders,

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and filters. Local deposition fractions within the 0.75 mm squares can be reported as the number of particles depositing within each square divided by either the total number of particles entering the geometry or the total number of deposited particles. In this study, local DFs in the G3-G5 model were based on the total number of particles entering the geometry. Local DFs on the inlet sampling insert were based on the total number of particles depositing on the insert. Both total and local DFs were multiplied by a factor of 100 and are reported as percentages.

2.3. CFD Methods The CFD package Fluent 12 (ANSYS Inc., Canonsburg, PA) was used to solve the governing equations of mass and momentum. User created Fortran code enabled the generation of an inlet particle profile from the experimentally determined inlet particle distribution, the processing of particle deposition files, and a user-defined surface roughness calculation. The outlet boundary conditions were matched to experimentally measured pressures from the in vitro model at the flow rate considered. The airway model was meshed entirely with hexahedral control volumes (Vinchurkar and Longest 2008) and consisted of 516,800 cells with increased mesh density near the walls. All terms in the governing equations for mass and momentum were discretized to be at least second order accurate using either 2nd order upwind or central difference approximations. For the steady state flow field considered, the SIMPLEC pressure coupling routine was implemented. Laminar solutions were considered due to the low inlet Reynolds number, 1882, and relatively large particle size, 10 μm. A solution was said to converge when the mass, momentum, and energy residuals dropped below 1 x 10-5. Further details of the CFD solution including the governing equations and solution procedure are described in previous

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publications on aerosol transport and deposition (Longest and Vinchurkar 2007b; Longest et al., 2006). A Lagrangian particle tracking algorithm was implemented to determine the transport and deposition of the 10 μm particles considered in this study. The Lagrangian transport equations can be expressed

dvi dt

f

Wp

 ui  vi  gi (1  D )

and

dxi dt

vi (t ) .

(1)

Here vi and ui are the components of the particle and local fluid velocity, gi denotes gravity, and  is the ratio of mixture to particle density /p. The characteristic time required for a particle to respond to changes in fluid motion, or the particle relaxation time, is expressed as Wp = Updp2/18P, where dp is the particle diameter and  is the absolute viscosity of the carrier fluid. The pressure gradient or acceleration term for aerosols was neglected due to small values of the density ratio. The drag factor f, which represents the ratio of the drag coefficient to Stokes drag, was based on the expression of Morsi and Alexander (1972). Effects of Brownian motion and turbulent dispersion were not included due to the simulation of particles greater than 1 μm and laminar flow conditions. The inlet distribution of particles was matched to the experimentally determined inlet particle concentrations, as described in the results. 10,000 particles were injected at the inlet of the converged flow field and were found to fully resolve particle deposition fractions. Three conditions of wall surface roughness were considered in the CFD airway model, which were smooth, coarse roughness, or fine roughness walls. These boundary conditions related only to particle capture and not to interactions with the flow field in this study. This assumption is reasonable for laminar flow where wall roughness has a minor effect on flow field conditions and will likely not be true for turbulent conditions. The smooth wall case assumes a 16

wall with no surface roughness, which is the typical CFD boundary condition. Under this condition, particles were deposited when the surface of the particle touched the surface of the wall. Numerically, this occurs when the particle center of mass is one particle radius away from the surface. As reported above, surface roughness heights were determined for the coated and sanded-coated geometries using a surface profilometer. These surface heights were used to define a capture distance for particle deposition in the CFD model, as previously implemented by Shi and Kleinstreuer (2007). This approach simply assumes a particle is deposited if the particle surface comes within the wall surface roughness height of the wall boundary. Measured surface roughness heights for the unaltered and sanded-coated prototypes were used to define CFD cases of coarse roughness and fine roughness walls, respectively. An association is expected between the coated (unsanded) experimental data and coarse CFD results (and the sanded-coated experimental data with the fine CFD predictions). However, the simplicity of the particle capture approximation will likely result in some differences between the experiments and predictions. Comparison of smooth, coarse, and fine CFD results will establish the effects of wall roughness boundary conditions on regional and local deposition predictions in the tracheobronchial region, which have not previously been considered.

3. Results

3.1. Inlet Particle Profile The number of deposited particles in each 0.75 mm x 0.75 mm grid cell was determined on the sampling insert. These deposition counts were converted to deposition fraction values calculated as the number depositing in each cell divided by the total number depositing on the insert (Figure 3b). To simplify the inlet particle boundary condition, the counted grid deposition

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fractions were used to determine the inlet distribution in terms of quadrants. Figure 3c shows the numerical particle inlet profile with the experimentally determined quadrant weighting of I = 17.5%, II = 17.5%, III = 38%, and IV = 27%. This profile uses the quadrant weighting determined by the experimental count coupled with a “blunt” particle profile to define the distribution in the radial direction, as previously described by Longest et al. (2006). In the numerical boundary condition, the separation distance between the particles and wall at the inlet was assumed to be 1 mm. This inlet profile was applied at the exit of the conical section shown in Figure 2b, which was the inlet of the double bifurcation model. For improved consistency between the experiments and CFD simulations, the conical nozzle was included as the flow inlet to the CFD model.

3.2. Measurement of Outlet Pressure and Surface Roughness The outlet pressures and surface roughnesses used in the CFD simulations were based on measurements of the in vitro system. From left to right of Figure 1 the measured outlet pressures were 8.026, 8.026, 8.103, and 8.077 centimeters of water. The surface roughness of the unaltered model was measured as Rq = 141.94 μm using the profilometer. Similarly, the surface roughness of the sanded-coated model was found to be 105.15 μm. Based on these measurements, a coarse surface roughness was approximated with a particle capture height of 142 μm. Similarly, a fine surface roughness was defined based on a particle capture height of 105 μm.

3.3. Deposition Fractions

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As described in the Introduction, deposition studies have been traditionally reported in large airway regions, and the largest region considered in this study is the asymmetric double bifurcation G3-G5. Experimentally determined total deposition fractions for the unaltered, coated, and sanded-coated experiments are shown in Figure 4a. The deposition fraction in the unaltered base in vitro model (DF = 27.80%) is significantly lower (approximate 61% relative difference) than with the coated and the sanded-coated models. Both the coated (DF = 51.60%) as well as the sanded-coated (DF = 52.89%) in vitro models have similar total deposition fractions (2.47% relative difference). Lower deposition in the unaltered in vitro model is likely due to particle bounce and re-entrainment, which is significantly reduced by the inclusion of the coating. As a result, coating of the in vitro models appears important to accurately capture the initial particle deposition field as it would occur in the respiratory airways, which are lined with mucus. In contrast, varying the surface roughness height by a factor of 1.35 does not appear to alter the total deposition fraction. CFD predictions for the base, coarse, and fine wall approximations are shown in Figure 4b. Based on CFD estimates, the deposition fraction increases with increasing roughness. Considering the smooth CFD case compared with the unaltered in vitro geometry, deposition is over-predicted by the CFD model. This difference is expected because the CFD model does not include particle bounce and re-entrainment. Comparing the CFD results across the range of wall roughnesses, simulating some level of wall roughness appears to have an effect on the solution. However, the total deposition is not sensitive to differences in wall roughness height in the range of 105 to 142 μm. Finally, comparison of experiments to CFD predictions with wall roughness included indicates a very good match (Figure 4c). Comparing the coated in vitro model and coarse CFD solution, the

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relative error in total DF is 6.0%. For the sanded experimental model and fine CFD case, the relative error between the total DF is 2.0%.

3.4. Highly Localized Deposition The localized deposition patterns are dramatically different between the three experimental cases as shown in Figure 5. Local DFs are calculated as the total number of deposited particles in each grid cell divided by the total number of particles entering the model and presented as a percentage. Figures 5b and 5c show a high density of deposition (local relative hotspot) at the first bifurcation and a less dense but still pronounced region of deposition near the bifurcation of the major daughter (left hand daughter bifurcation in the figure). In contrast, Figure 5a shows a dense region of particles near the first bifurcation, but shifted off the peak and down the minor daughter. This shift in peak local deposition away from the carina may imply particle rolling, which could occur due to expected high shear stresses in this area. Local deposition within hotspots appears similar between the coated and sanded-coated in vitro models (Figures 5b vs. 5c). However, it appears that sanding reduced local deposition in all areas except for the carinal ridges. As indicated in Figure 4, this reduction in local deposition does not appreciably change the total deposition values for the double bifurcation geometry and coarse micrometer particles. For comparison with experimental local deposition results, the corresponding CFD results projected on a 2D grid equivalent to the 0.75 mm x 0.75 mm reticle squares are shown in Figure 6. Similarities in the deposition patterns are observed between the experimental and CFD results. Specifically, with the CFD results, primary deposition occurs at the first bifurcation with

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a second less dense region of deposition occurring at the bifurcation within the major daughter. Another similarity between the experimental data and predictions is that the CFD model indicates a less dense region extending away from the first carina down the minor daughter branch. Among the CFD cases, the densest cluster of deposition occurs at the first carina of the coarse model (Figure 6b). A geometry divided by the midplane perpendicular to gravity was required for optical determination of highly localized deposition. Resulting top and bottom half deposition fractions within the geometry provide additional data for validating the simulations. Figure 7 compares the localized deposition values between the experimental (coated) and CFD (fine wall roughness) models. Similarities are observed between the experimental data and CFD predictions of local deposition for both the top and bottom halves of the geometry. The primary and secondary regions of deposition are the first bifurcation and the major daughter bifurcation, respectively, based on both the experiments and simulations. However, the CFD model predicts a minor hot spot of deposition at the ridge of the minor daughter, which is not present in the experimental results. This difference may be due to post-deposition spreading of the aerosol in the experiments or inaccuracies in the inlet particle profile used in the simulations. Comparison of the experimental (coated) and CFD (coarse wall roughness) cases results in the same observations.

3.5. Cumulative Local Deposition The highly localized data for the cases considered are represented as cumulative line graphs of deposition fraction in Figure 8. The line graphs sum all deposition fractions at values of constant x (or y) and present the data as a cumulative total. For Figure 8a, deposition fractions

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are determined by summing all values across 0.75 mm bins of constant x and accumulating these values in the x-direction. Figure 8b presents values for bins of constant y and accumulating in the y-direction. First, relatively large differences are observed between the experimental coated and experimental sanded-coated models in both x- and y-directions. Small differences in deposition are observed between the CFD predictions for coarse and fine wall surface roughness. The coated in vitro model results agree with both CFD predictions better than the sanded-coated results in x- and y-directions. This implies that sanding altered the geometry in ways that were not fully included in the CFD geometry. Overall, agreement between the coated in vitro experiments and CFD predictions is good. Some small differences occur between the predictions and coated experimental results in the region of 1 cm in the x-direction and 1.5 cm in the ydirection. However, these differences can be largely reduced if the geometry is shifted by one or two grid cells in either direction. In summary, local deposition on a cumulative basis in the xand y-directions for the coated in vitro model is captured well by the CFD simulations with coarse or fine wall conditions. Another way of visualizing the local deposition information is to look at the deposition fractions in bins with widths of 0.75 mm in the x- and y-directions that are not totaled as cumulative sums. This provides a bin by bin comparison of the data presented in Figure 8 without a cumulative sum of the deposition fractions. The coated in vitro model and the coarse CFD predictions are compared in Figure 9 and qualitative agreement is shown between the shape of the experimental and CFD deposition results. However, relative differences within some bins are large. The CFD simulations tend to predict higher peaks in deposition compared with the experiments at values of constant x and y. Furthermore, the CFD model predicts regions of

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elevated deposition further upstream compared with the experimental results. This may imply some post-deposition spreading of the particles due to wall shear stresses in the experiments. Deposition enhancement factors (DEF) are presented in Figure 10 for the coated experimental case and coarse CFD simulations. In this study, DEF values are calculated as the local DF divided by the total DF for the geometry based on the 2D experimental sampling grid. As an example, a DEF of 40 indicates that 40x more deposition occurs in one sample location than in the geometry on an average basis. The DEF values are similar in trend and magnitude between the experiment (Figure 10a) and CFD simulations (Figure 10b). Maximums at the main carina are both above 40 for the simulations and experiment. One difference is that the CFD predicts higher DEF values at the second bifurcation carina compared with the experiment. This observation is consistent with post-deposition spreading of the aerosol in the experiment. Local deposition between the experimental results and CFD simulations is further compared in Tables 2 and 3. Table 2 presents the number of cells for each analysis that have DFs of specific values. Considering the coated experiment vs. the coarse CFD, trends in the number of deposited particles per cell are generally similar except for the case of DFs greater than 3. For this maximum deposition fraction per cell, the coated experiment has three cells whereas the CFD simulation only has one cell. In Table 3, total DF, maximum DF, and maximum DEF of all 2D counting grid cells in the geometry are reported. As previously indicated, the coated experiments and CFD simulations are in good agreement for total DF. However, the maximum DF and maximum DEF values are lower for the CFD cases. These maximums all occur at the first bifurcation. The fact that higher DF and DEF maximum values are observed in the experiments suggests that rolling and post-deposition spreading may not be occurring at the first bifurcation. Furthermore, the higher local values in the experiments of DF

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and DEF maximum indicate that CFD simulations are under-predicting local deposition. Therefore, local maximum DEF values may be even higher than previously reported in CFD studies.

4. Discussion and Conclusions

The primary objective of this study was to provide new regional and highly localized in vitro data on the deposition of micrometer particles in a reproducible and fully defined asymmetrical double bifurcation geometry. Deposition was considered throughout the geometry and on a highly localized basis using a sub-millimeter grid as a function of surface coating and surface roughness. This study provides a significant extension to previous work on highly localized deposition considering that a new asymmetrical bifurcating geometry was implemented, which is consistent with typical bifurcations in humans, and the effects of surface properties were included. The in vitro results provide valuable knowledge related to the formation of hotspots in an asymmetrical geometry and the magnitude of hotspots in terms of DEF as a function of surface properties. For example, Table 3 indicates that sanding the in vitro model increases the maximum DEF value by approximately 10%. The highly localized deposition results also provide a valuable dataset for validating CFD predictions of particle deposition in a well defined geometry with a measured particle inlet profile. A primary outcome of this study is the finding that coating the experimental hard plastic in vitro model is important to capture both the total and local deposition at the site of particlewall contact. For both impactor studies and pharmaceutical aerosol deposition using in vitro models, coating the geometry is typically performed (Delvadia et al., 2010; Kamiya et al., 2004; Tian et al., 2011b). However, previous in vitro studies employing soft cast models of the

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airways have often not used a surface coating (Longest and Oldham 2006; Longest and Oldham 2008; Oldham et al., 2000), based on the previous finding that it was not needed for silicone based models (Oldham et al., 1997). Results of the current study indicate a 61% lower relative difference in deposition for the uncoated hard plastic in vitro model compared with surface coatings. The most likely explanation for this reduction in deposition is that particles striking the uncoated surface have a higher probability to rebound back into the airstream, roll after deposition, or be re-entrained in regions of high shear. These effects are largely reduced with surface coating. The absence of surface coating also affected the local deposition patterns and strength of hot spots. As observed in Figure 5, the hot spot at the first carina appears to have migrated down the minor daughter branch and is an order of magnitude lower than with cases employing surface coating. Findings of this study highlight the need to coat hard plastic in vitro models when conducting deposition studies using particles. In contrast, previous local deposition studies (Longest and Oldham 2006; Longest and Oldham 2008; Oldham et al., 2000) have employed flexible silicone-based in vitro geometries without surface coatings. Comparisons between CFD predictions and these previous experimental datasets of total and local deposition are very good. These previous CFD models assume smooth walls and perfect capture at particle-wall contact. As a result, it appears that coating flexible models is less important when considering deposition with in vitro geometries, likely because of reduced particle rebound. Considering properties of the particles, both this study and the previous local deposition studies of Longest and Oldham (2006; 2008) have employed polystyrene latex spheres. Coating hard in vitro model airways is also likely important for evaluating the deposition of pharmaceutical dry powders (Delvadia et al., 2012). However, coating will not likely affect the deposition of droplets from spray aerosols

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when using in vitro geometries (Longest and Hindle 2009a; Longest and Hindle 2009b; Longest et al., 2007; Longest et al., 2008). It is not clear if coating hard plastic models is necessary for the deposition of particles smaller than the 10 μm spheres employed in this study, as smaller particles will have less rebound potential. In contrast with coating, the degree of surface roughness over the scales considered indicates a minor effect on deposition for laminar flow. Specifically, reducing the airway surface roughness from 142 μm to 105 μm was associated with a negligible (1.3%) change in total deposition and an approximately 10% change in maximum DEF. CFD results indicated that the inclusion of some surface roughness in the deposition condition was important to capture the in vitro deposition data, but results were not sensitive to the two levels of roughness considered (Figure 4b). Clearly, surface roughness will become more significant as the flow rate is increased and turbulent dispersion becomes a stronger deposition mechanism. It is noted that turbulent dispersion is dependent on both the magnitude of turbulence and the size of the particle diameter with maximum effects typically around 4 μm. It is expected that the findings of Kelly et al. (2004a) on surface roughness in the nasal airways arise from increased turbulent dispersion associated with rough walls. However, this previous finding does not appear to translate to the tracheobronchial region beginning at G3 even with a tracheal flow rate of 60 LPM. Considering future local deposition studies of solid particles in hard plastic in vitro models, it appears critical that a coating be applied, but much less important to sand the internal geometry. Coating may also provide some uniformity to the local surface characteristics. It is advantageous that coating is the more important factor as internal geometries can be easily coated whereas internal sanding and surface tolerance control are more difficult and technically challenging.

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As a secondary objective, CFD results were compared with the in vitro data in terms of predicting both the total and local deposition. A very simple wall boundary approximation of surface roughness was implemented in which particles were assumed to deposit when they came within the wall surface roughness height, as previously implemented by Shi et al. (2007). The CFD simulations with this wall roughness approximation capture total deposition in the double bifurcation geometry very well. Agreement was adequate between in vitro data and CFD predictions in terms of qualitative local deposition patterns and cumulative deposition in increments of 0.75 mm in the x- and y-directions. However, larger differences were observed between the in vitro results and CFD predictions in terms of magnitude of hotspots in the daughter branches, maximum DEFs, and local DFs in individual 0.75 mm cells. Some potential particle rolling or silicone oil migration even in the coated in vitro models may make exact quantitative agreement at the sub-millimeter scale a great challenge. However, limitations of the CFD model are likely responsible for some of the discrepancy between the predictions and experimental data. As described, quantitative comparisons of local deposition at the sub-millimeter level highlight potential limitations of the CFD model. Inaccuracies in the CFD simulation may arise from the assumption that the flow field is laminar and that wall roughness does not influence the flow. Previously, Longest and Vinchurkar (2007b) demonstrated differences in local deposition between laminar and turbulent solutions in a symmetric bifurcation of G3-G5 at a tracheal flow rate of 60 LPM. The occurrence of transitional and turbulent flow will be enhanced by wall roughness of the in vitro model. Considering particle transport, simplifying the inlet profile into quadrants likely reduces the accuracy of the local deposition results and may explain why hotspots occur in the minor daughter with the simulations but not with the experiments. Other

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limiting assumptions include the particle capture approximation and the absence of rolling or coating migration due to high shear stress. Future studies are needed to explore the effects of these assumptions in order to determine if the local deposition pattern can be better matched with current CFD capabilities. However, an interesting finding is that the CFD models consistently under-predict the maximum DF and DEF of the experiments, even for the coated and sanded in vitro models. This implies that the CFD model provides a conservative under-prediction of local deposition and hotspots compared with the experiments. Therefore, actual maximum DEFs in the airways may be even higher than previously predicted in CFD simulation studies that quantify hotspot magnitudes (Balashazy et al., 2003; Longest et al., 2006; Xi et al., 2008; Zhang et al., 2005). Considering the experimental setup, a number of factors contribute to the differences between the in vitro system and in vivo conditions. The complexity of the human lung in vivo was reduced to a double-bifurcation unit to provide a sample region of evaluation and comparison (Kleinstreuer and Zhang 2009; Longest and Oldham 2006; Longest and Oldham 2008). Asymmetry has been introduced into this system and further work should be done to examine the impact of asymmetry on localized deposition. The transient inhalation pattern exhibited by the patient will also produce variations in deposition (Gurman et al., 1984; Kim and Jaques 2004; Schlesinger et al., 1982) that should be controlled by matching inlet Reynolds and Stokes numbers (Zhang et al., 2002). The coupling of the air flow and movement of the bifurcation walls provides addition complications typically considered near the alveolar region (Berg and Robinson 2011; Haber and Tsuda 2006; Longest and Holbrook 2012). These factors should be taken into account when translating the reported local deposition data to in vivo conditions.

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In conclusion, this study has provided a valuable new dataset for understanding the effects of surface characteristics on local deposition, assessing hotspot magnitude in the tracheobronchial airways, and validating CFD predictions. The importance of coating hard in vitro geometries was established while surface roughness played a less significant role in the total and local deposition patterns. Within the simple geometry employed, CFD adequately predicted total deposition, qualitative patterns, and cumulative deposition. However, inaccuracies were observed in the quantitative sub-millimeter prediction of deposition and maximum local DEF values. Future CFD studies are needed to improve agreement with experimental results on a highly localized basis. Using the established in vitro system for local deposition, future experimental studies will explore the effects of different particle sizes, flow rates, and inlet conditions from more realistic composite geometries.

ACKNOWLEDGMENTS

Dr. Michael Oldham is gratefully acknowledged for providing technical expertise in setting up the experimental system and helpful conversations. LH acknowledges financial support from an NSF GAANN fellowship. This work was supported in part with funds from US FDA grant U01 FD004570

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Figure 1.

Asymmetric double bifurcation geometry including Generations 3 – 5 (trachea is G0) of the human tracheobronchial airways presented as (a) the 3D surface used for CFD mesh construction and (b) the in vitro model prototyped in a Viper SLA machine with added ¼ inch external barbs and a build layer height of 0.1 mm.

Figure 2.

Experimental setup for generating 10 μm fluorescent particles at an inlet flow rate of 7.5 LPM including (a) a schematic of the experimental system and (b) the custom interface between the Kr-85 neutralizer and the prototyped geometries with a conical nozzle leading to the in vitro model inlet.

Figure 3.

(a) Sampling insert positioned at the exit of the aerosol generation apparatus to quantify the cross-sectional inlet particle distribution entering the double bifurcation in vitro model. (b) Experimentally determined deposition fractions (%) from counting particles depositing on the horizontal bars of the sampling insert performed in experiments separate from those used to determine deposition in the bifurcation geometry. (c) Numerical approximation of the inlet particle distribution that divides the experimental deposition fractions into four quadrants of different weights, each with a blunt particle inlet profile in the radial direction.

Figure 4.

Total deposition fractions (%) in the airway geometry including (a) the experimental results, (b) the CFD predictions, and (c) a comparison of experimental (coated and sanded-coated) with CFD (coarse and fine wall roughness) results.

Figure 5.

Highly localized deposition resolved on a 0.75 mm x 0.75 mm grid within the G3G5 geometry based on in vitro experiments for the (a) unaltered, (b) coated, and (c) sanded-coated cases.

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Figure 6.

Highly localized deposition resolved on a 0.75 mm x 0.75 mm grid projected on the numerical solution for the G3-G5 asymmetrical geometry with (a) smooth, (b) coarse, and (c) fine surface roughness conditions.

Figure 7.

Highly localized deposition for the experimental coated and CFD fine conditions subdivided into (a and b) top and (c and d) bottom halves of the geometry. Lefthand panels (a and c) represent experimental conditions and right-hand panels (b and d) represent CFD predictions. The gravity vector pointed from the top to the bottom half of the geometry.

Figure 8.

Cumulative deposition fractions (%) determined by (a) summing values across 0.75 mm bands of constant x and accumulating in the x-direction, and (b) summing values across 0.75 mm bands of constant y and accumulating in the y-direction. The coordinates used are shown in Figure 1 with the x-axis originating on the left hand side of the model and the y-axis originating at the center of the G3 inlet.

Figure 9.

Deposition fractions (%) determined by (a) summing values across 0.75 mm bands of constant x, and (b) summing values across 0.75 mm bands of constant y. The coordinates used are shown in Figure 1 with the x-axis originating on the left hand side of the model and the y-axis originating at the center of the G3 inlet.

Figure 10. Localized deposition enhancement factor (DEF) calculated on the 2D 0.75 mm x 0.75 mm grid compared between the (a) coated experimental model and the (b) coarse CFD predictions.

37

Table 1: Geometric parameters of the asymmetric bifurcation geometry. Generation

Diameter (cm)

L/D Phalen et al. (1978) N/A 2.36 2.45 2.55 2.5

Lengtha (cm)

Branching Curvature Ratio

Branch Angle

G3 0.5600 0.8300 N/A N/A G4 Major 0.4852 1.1451 8.7 15 G5 MajorLeft 0.4185 1.0252 8.7 15 G5 MinorLeft 0.3578 0.9122 2.8 55 G4 Minor 0.4148 1.3149b 2.8 55 G5 0.3578 2.8 1.0016 8.7 15 MajorRight G5 0.3059 2.8 0.8563 2.8 55 MinorRight a: Length is calculated from diameter multiplied by the L/D ratio of Phalen et al. (1978)

Carinal Curvature Ratio 0.1 0.1 0.1 0.1 0.1 0.1 0.1

b: Length of G4 Minor is greater than calculated due to the bifurcation construction technique

Table 2: Number of 0.75 mm x 0.75 mm grid cells with specified deposition fraction values.

Deposition Fraction (%)

0

>0 - 0.5 >0.5 - 1 >1 - 2 >2 - 3 >3

Coated Experiment

1117

221

8

6

5

3

Sanded-Coated Experiment 1192

147

6

9

3

3

Coarse CFD

1098

233

19

5

4

1

Fine CFD

1086

246

18

6

3

1

Table 3: Total deposition fraction, maximum deposition fraction, and maximum deposition enhancement factor (DEF) for the in vitro experiments (coated and sanded-coated) and CFD simulations (coarse and fine wall roughness).

Model

DFsum % DFmax

DEFmax

% Coated Experiment

51.60

5.46

69.34

Sanded-Coated Experiment

52.89

6.49

80.37

Coarse CFD

54.72

3.65

43.69

38

Fine CFD

51.81

3.34

42.23

Highlights

x

Provides a highly localized data set of aerosol deposition for validating CFD simulations

x

Hard plastic models should be coated to adequately capture total and local deposition

x

CFD simulations including wall roughness improve comparisons with in vitro results

x

Cell by cell comparisons indicate that local maximum DEF is higher in the in vitro experiments

x

Previous CFD estimates of local maximum DEF values may be conservatively low

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