Abstr:AC7-01: Difference between revisions
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Revision as of 11:20, 10 October 2019
Aerosol deposition in the human upper airways
Application Area 7: Biomedical Flows
Application Challenge AC7-01
Abstract
Knowledge of deposition characteristics in the human airways is important when assessing the impact of inhaled aerosols, that can be either atmospheric pollutants or aerosols intended for therapeutic purposes. Not only the total deposition, but also local depositions within individual parts of the lung are of interest. The application of computer models that are based on computational fluid dynamics for the prediction of aerosol deposition in the human airways has become very common nowadays. Despite their limitations, that are mainly associated to their high computational cost, CFD models offer significant advantages over in vitro / in vivo experiments. However, prior to their use CFD models need to be properly validated. This is the objective of the current application Challenge. Specifically, in vitro deposition measurements using positron emission tomography (PET) have been conducted in a human-based model of the upper airway during steady-state inhalation at flow rates of 15, 30 and 60 L/min. The flow conditions at these flowrates are in the transitional to turbulent regime. CFD simulations were carried out in the same geometry and under the same ventilation conditions. Two sets of simulations were performed: Large Eddy Simulations using the dynamic version of the Smagorinsky-Lilly subgrid scale model and RANS simulations using the k-ω-SST turbulence model. In both methods, the Lagrangian approach has been adopted to track spherical particles in the airway geometry and determine regional deposition patterns.
The methods and results described in the present Application Challenge are mainly adopted from Lizal et al. (2012) (experimental part) and Koullapis et al. (2018) (numerical part).
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Contributed by: P. Koullapis, F. Lizal, J. Jedelsky, L. Nicolaou, K. Bauer, O. Sgrott, M. Jicha, M. Sommerfeld, S. C. Kassinos — University of Cyprus
© copyright ERCOFTAC 2019