In Silico Fit Evaluation of Additively Manufactured Face Coverings.
Ian A Carr, Gavin D'Souza, Ming Xu, Shailesh Ozarkar, Daniel Porter, Marc Horner, Prasanna Hariharan
Author Information
Ian A Carr: Division of Applied Mechanics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, United States Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA. ian.carr@fda.hhs.gov. ORCID
Gavin D'Souza: Division of Applied Mechanics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, United States Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA.
Ming Xu: Ansys Inc., 1007 Church Street, Suite 250, Evanston, IL, 60201, USA.
Shailesh Ozarkar: Ansys Inc., 1007 Church Street, Suite 250, Evanston, IL, 60201, USA.
Daniel Porter: Division of Applied Mechanics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, United States Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA.
Marc Horner: Ansys Inc., 1007 Church Street, Suite 250, Evanston, IL, 60201, USA.
Prasanna Hariharan: Division of Applied Mechanics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, United States Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA.
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.
