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Simple Models of Face Mask Aerodynamics to Quantify Effects of Peripheral Leaks on Mask Effectiveness

ORAL

Abstract

Face masks continue to be at the front lines of our defense against COVID-19. Studies have shown that the filtration effectiveness (fractional blockage of respiratory droplets) depends not only on the cloth/fabric/material employed in the face mask but also the "fit" of the mask on the face. Most of the face masks worn by people have peripheral leaks, which can significantly diminish the filtration effectiveness of the masks. In the current study, we combine a simple lumped-element model of face mask aerodynamics with (a) numerical data from computational models of face mask deployment on realistic faces, and (b) experimental data on permeability and filtration efficiency of various cloths/fabrics, to quantify the filtration effectiveness of various masks. Results show that even with small peripheral gaps, the leaks through the periphery can reach a considerable proportion of the total respiratory volume flow rate, resulting in reduced filtration effectiveness. It is also found that the permeability of the mask material plays a significant role in determining the overall filtration effectiveness of face masks. The implications of these findings for the design of more effective face masks are discussed.

Presenters

  • Chuanxin Ni

    Johns Hopkins University

Authors

  • Chuanxin Ni

    Johns Hopkins University

  • Tomas Solano

    Florida State University

  • Tso-Kang Wang

    Florida State University

  • Jung-Hee Seo

    Johns Hopkins University, Johns Hopkins Univ

  • Kourosh Shoele

    Florida State University, Joint College of Engineering, Florida A&M University-Florida State University, Department of Mechanical Engineering, Florida State University, florida state university, FAMU-FSU College of Engineering

  • Kenny Breuer

    Center for Fluid Mechanics, School of Engineering, Brown University, Providence RI, Brown, Center for Fluid Mechanics, Brown University, Center for Fluid Mechanics, School of Engineering, Brown University, Brown University

  • Rajat Mittal

    Johns Hopkins University