10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
Abstract View
Validating CFD Predictions of Small Particle Aerosol Deposition in a Infant Nasal Airway Model
KARL BASS, Susan Boc, Michael Hindle, Worth Longest, Virginia Commonwealth University
Abstract Number: 393 Working Group: Aerosols in Medicine
Abstract Nose-to-lung (N2L) administration of enhanced excipient growth (EEG) particles or droplets is expected to increase lung dose and improve targeted delivery of treatments for infants with respiratory diseases, such as Cystic Fibrosis (CF) and Respiratory Syncytial Virus (RSV). With EEG delivery, small particles or droplets (<2µm) enter the nasal cavity via a streamlined nasal cannula and are able to penetrate to the lower airways due to decreased impaction deposition. The hygroscopic excipient of these particles/droplets allows them to absorb moisture in the humid airway conditions and hence increase in diameter, which leads to increased deposition deep in the lungs. The use of CFD and in vitro models has proven a valuable tool to progress the development of the condensational growth approaches for pharmaceutical aerosol delivery. The CFD model must be validated against experimental data to ensure accuracy of the numerical results, and provides greater insight into the transport physics and particle/droplet deposition sites. The objective of this study was to validate mesh and solution parameters against experimental data for accurate modelling of microparticle deposition in an infant nasal airway for the assessment of N2L aerosol administration. The infant nasal model was generated by segmentation of CT scans in the Mimics and 3-matic software packages, and a CAD model developed in SolidWorks. The scan was chosen from an in-house database using selection criteria that are representative of a six-month-old infant: height and weight were between the 25th and 75th percentile, the mouth was closed as is typical during nasal drug administration, and the scan resolution was sufficient to build an accurate model. A Stratasys Objet 24 3D printer was used to build the experimental model, which included connections for the streamlined nasal cannula and outlet filter. A set of CFD meshing and solution guidelines, which were previously developed by our group for aerosol deposition in low Reynolds number and transitional turbulence, were applied to the CFD model in an effort to ensure accurate and reliable results. The CFD model was meshed and transport equations were solved using the capabilities provided by the ANSYS software suite of products with additional in-house user codes to address near-wall turbulence and particle-wall interactions. Comparisons are made between different meshing strategies, such as tetrahedral, cut-cell, and polyhedral cells, mono- and poly-disperse particle size distributions, and laminar or k-omega flow models. Furthermore, a wall roughness model is included to evaluate its accuracy compared to experimental pressure drop, and the effect on the near-wall velocity and turbulence fields. Application of predetermined CFD model guidelines provided results that compared well with experimental deposition data. The results also demonstrate that the two-equation k-omega model is capable of accurately capturing microparticle deposition, without the need for more complex turbulence models. As expected, the low nasal deposition of small EEG particles leads to high lung dose, with more that 90% of particles exiting the experimental and CFD model outlet. This study provides further validation of our previously developed meshing and solution guidelines, with good comparisons drawn between CFD and experimental deposition data in the complexities of an infant nasal model. The CFD model also utilized the wall roughness model, which provides a more realistic representation of the physical characteristics of the in vitro model wall surfaces, and is known to influence the skin friction, pressure drop, and near-wall flow field. For medical applications, the particle deposition data shows that the N2L EEG approach to aerosol delivery provides a highly efficient and targeted method of respiratory drug delivery to infants.