In Silico Fit Evaluation of Additively Manufactured Face Coverings

In response to the respiratory protection device shortage during the COVID-19 pandemic, the additive manufacturing (AM) community designed and disseminated numerous AM face masks. Questions regarding the effectiveness of AM masks arose because these masks were often designed with limited (if any) fu...

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Veröffentlicht in:Annals of biomedical engineering 2023-01, Vol.51 (1), p.34-44
Hauptverfasser: Carr, Ian A., D’Souza, Gavin, Xu, Ming, Ozarkar, Shailesh, Porter, Daniel, Horner, Marc, Hariharan, Prasanna
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container_end_page 44
container_issue 1
container_start_page 34
container_title Annals of biomedical engineering
container_volume 51
creator Carr, Ian A.
D’Souza, Gavin
Xu, Ming
Ozarkar, Shailesh
Porter, Daniel
Horner, Marc
Hariharan, Prasanna
description In response to the respiratory protection device shortage during the COVID-19 pandemic, the additive manufacturing (AM) community designed and disseminated numerous AM face masks. Questions regarding the effectiveness of AM masks arose because these masks were often designed with limited (if any) functional performance evaluation. In this study, we present a fit evaluation methodology in which AM face masks are virtually donned on a standard digital headform using finite element-based numerical simulations. We then extract contour plots to visualize the contact patches and gaps and quantify the leakage surface area for each mask frame. We also use the methodology to evaluate the effects of adding a foam gasket and variable face mask sizing, and finally propose a series of best practices. Herein, the methodology is focused only on characterizing the fit of AM mask frames and does not considering filter material or overall performance. We found that AM face masks may provide a sufficiently good fit if the sizing is appropriate and if a sealing gasket material is present to fill the gaps between the mask and face. Without these precautions, the rigid nature of AM materials combined with the wide variation in facial morphology likely results in large gaps and insufficient adaptability to varying user conditions which may render the AM face masks ineffective.
doi_str_mv 10.1007/s10439-022-03026-8
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subjects Adaptability
Additive manufacturing
Best practice
Biochemistry
Biological and Medical Physics
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Biophysics
Classical Mechanics
COVID-19
COVID-19 - epidemiology
COVID-19 - prevention & control
Design
Face
Humans
Masks
Mathematical analysis
Methodology
Pandemics
Pandemics - prevention & control
Performance evaluation
Protective equipment
S.I. : Modeling for Advancing Regulatory Science
SARS-CoV-2
Sizing
title In Silico Fit Evaluation of Additively Manufactured Face Coverings
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