Description AC7-01
Aerosol deposition in the human upper airways
Application Challenge AC7-01 © copyright ERCOFTAC 2019
Description
Introduction
The objective of the current application Challenge is to present a benchmark case that can
be used for the validation of computational tools intended for regional deposition studies in
the upper airways. In the present application Challenge, in vitro deposition measurements
in a complex realistic geometry are provided at various inhalation flow rates. CFD results
are then compared against the measured data. Since deposition in the upper airways
is determined by the airflow features, a second application Challenge will follow where
airflow measurements using Particle Image Velocimetry (PIV) are reported in the same
geometry. These will again be compared against the LES and RANS predictions. In this
manner, a complete benchmark case for the validation of computational packages intended
for deposition predictions in the upper airways will be established and made available to
the wider community. Furthermore, best practice guidelines for numerical predictions of
regional deposition in the airways, which can assist in the design and optimization of
inhalation therapies, will be provided.
In the current application Challenge, the in vitro deposition measurements have been
conducted in a human—based model of the upper airways, shown in figure 3, using positron
emission tomography (PET). The experiments were performed at steady—state inhalation
with flow rates of 157 30 and 60 L/min. The flow conditions at these flowrates are in the
transitional t0 turbulent regime. The CFD simulations were carried out in the same geom—
etry 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—w—SST model. In both methods7 the Lagrangian
approach has been adopted to track spherical particles in the airway geometry and de—
termine 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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© copyright ERCOFTAC 2019