Computational modelling of an aerosol extraction device for use in COVID-19 surgical tracheotomy
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
In view of the ongoing COVID-19 pandemic and its effects on global health, understanding and accurately modelling the propagation of human biological aerosols has become crucial. Worldwide, health professionals have been one of the most affected demographics, representing approximately 20% of all cases in Spain, 10% in Italy and 4% in China and US. Methods to contain and remove potentially infected aerosols during Aerosol Generating Procedures (AGPs) near source offer advantages in reducing the contamination of protective clothing and the surrounding theatre equipment and space. In this work we describe the application of computational fluid dynamics in assessing the performance of a prototype extraction hood as a means to contain a high speed aerosol jet. Whilst the particular prototype device is intended to be used during tracheotomies, which are increasingly common in the wake of COVID-19, the underlying physics can be adapted to design similar machines for other AGPs. Computational modelling aspect of this study was largely carried out by Barcelona Supercomputing Center using the high performance computational mechanics code Alya. Based on the high fidelity LES coupled with Lagrangian frameworks the results demonstrate high containment efficiency of generated particles is feasible with achievable air extraction rates.
Date Issued
2022-01-01
Date Acceptance
2021-07-12
Citation
Journal of Aerosol Science, 2022, 159
ISSN
0021-8502
Publisher
Elsevier
Journal / Book Title
Journal of Aerosol Science
Volume
159
Copyright Statement
© 2021 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Subjects
0306 Physical Chemistry (incl. Structural)
0401 Atmospheric Sciences
0904 Chemical Engineering
Meteorology & Atmospheric Sciences
Publication Status
Published
Article Number
ARTN 105848
Date Publish Online
2021-07-27