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 Challenge7 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 features7 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 manner7 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. Furthermore7 best practice guidelines for numerical predictions of regional deposition in the airways7 which can assist in the design and optimization of inhalation therapies7 will be provided.

In the current application Challenge, the in vitro deposition measurements have been conducted in a human—based model of the upper airways7 shown in ﬁgure 37 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)

Contributed by: *** — ***