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__NOTOC__
__NOTOC__
=Aerosol deposition in the human upper airways=
=Aerosol deposition in the human upper airways=
==Application Area 7: *****==
==Application Area 7: Biomedical Flows==
===Application Challenge AC7-01===
===Application Challenge AC7-01===
=Abstract=
=Abstract=
Knowledge of deposition Characteristics in the human airways is important When assessing
Knowledge of deposition characteristics in the human airways is important when assessing
the impact of inhaled aerosols7 that can be either atmospheric pollutants 0r aerosols in—
the impact of inhaled aerosols, that can be either atmospheric pollutants or aerosols
tended for therapeutic purposes. Not only the total deposition7 but also local depositions
intended for therapeutic purposes.
Within individual parts of the lung are of interest. The application of computer models
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
that are based on computational fluid dynamics for the prediction of aerosol deposition in
the human airways has become very common nowadays. Despite their limitations7 that
the human airways has become very common nowadays. Despite their limitations, that
are mainly associated to their high computational cost7 CFD models offer significant ad—
are mainly associated to their high computational cost, CFD models offer significant advantages
vantages over in vitm / in vivo experiments. However7 prior to their use CFD models
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.
need to be properly validated. This is the objective of the current application Challenge.
Specifically7 in vitm 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 airways during steady-state
inhalation at flow rates of 157 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 [[Best_Practice_Advice_AC7-01#lizal2012|Lizal ''et al.'' (2012)]] (experimental part)
part).
and [[Best_Practice_Advice_AC7-01#koullapis2018|Koullapis ''et al.'' (2018)]] (numerical part),
reporting on work carried out in  COST Action MP1404 SimInhale
'Simulation and pharmaceutical technologies for advanced patient-tailored inhaled
medicines’. http://www.siminhale-cost.eu
 
 
<div id="figure0"></div>
{|align="center" border=0
|-
|align="center"|[[Image:AC7-01_fig0.png|408px]]
|}
<br/>
<br/>
----
----
{{ACContribs
{{ACContribs
|authors=P. Koullapis
|authors=P. Koullapis<sup>a</sup>, F. Lizal<sup>b</sup>, J. Jedelsky<sup>b</sup>, L. Nicolaou<sup>c</sup>, K. Bauer<sup>d</sup>, O. Sgrott<sup>e</sup>, M. Jicha<sup>b</sup>, M. Sommerfeld<sup>e</sup>, S. C. Kassinos<sup>a</sup>
|organisation=***
|organisation=<br><sup>a</sup>Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus<br><sup>b</sup>Faculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic<br><sup>c</sup>Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, USA<br><sup>d</sup>Institute of Mechanics and Fluid Dynamics, TU Bergakademie Freiberg, Freiberg, Germany<br><sup>e</sup>Institute Process Engineering, Otto von Guericke University, Halle (Saale), Germany
}}
}}
{{ACHeader
{{ACHeader

Latest revision as of 10:41, 21 October 2019

Front Page

Description

Test Data

CFD Simulations

Evaluation

Best Practice Advice

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 airways 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), reporting on work carried out in COST Action MP1404 SimInhale 'Simulation and pharmaceutical technologies for advanced patient-tailored inhaled medicines’. http://www.siminhale-cost.eu


AC7-01 fig0.png




Contributed by: P. Koullapisa, F. Lizalb, J. Jedelskyb, L. Nicolaouc, K. Bauerd, O. Sgrotte, M. Jichab, M. Sommerfelde, S. C. Kassinosa — 
aDepartment of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus
bFaculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic
cDivision of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, USA
dInstitute of Mechanics and Fluid Dynamics, TU Bergakademie Freiberg, Freiberg, Germany
eInstitute Process Engineering, Otto von Guericke University, Halle (Saale), Germany

Front Page

Description

Test Data

CFD Simulations

Evaluation

Best Practice Advice


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