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need to be properly validated. This is the objective of the current application Challenge.
need to be properly validated. This is the objective of the current application Challenge.
Specifically, ''in vitro'' deposition measurements using positron emission tomography (PET)
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
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
inhalation at flow rates of 15, 30 and 60 L/min.
are in the transitional t0 turbulent regime. CFD simulations were carried out in the
The flow conditions at these flowrates are in the transitional to turbulent regime.
same geometry and under the same ventilation conditions. Two sets of simulations were
CFD simulations were carried out in the same geometry and under the same ventilation conditions.
performed: Large Eddy Simulations using the dynamic version of the Smagorinsky—Lilly
Two sets of simulations were performed:
subgrid scale model and RANS simulations using the k—w—SST turbulence model. In both
Large Eddy Simulations using the dynamic version of the Smagorinsky-Lilly
methods7 the Lagrangian approach has been adopted to track spherical particles in the
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.
airway geometry and determine regional deposition patterns.


The methods and results described in the present Application Challenge are mainly
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
adopted from Lizal ''et al.'' (2012) (experimental part)
part).
and Koullapis ''et al.'' (2018) (numerical part).
<br/>
<br/>
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Revision as of 08:48, 2 October 2019

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Evaluation

Best Practice Advice

Aerosol deposition in the human upper airways

Application Area 7: *****

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).



Contributed by: P. Koullapis — ***

Front Page

Description

Test Data

CFD Simulations

Evaluation

Best Practice Advice


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