In Silico Fit Evaluation of Additively Manufactured Face Coverings
Ian A Carr1, Gavin D'Souza2, Ming Xu3
1Division 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.
Annals of Biomedical Engineering
|July 28, 2022
Summary
Additive manufacturing (AM) face masks may fit well if properly sized and include a gasket. Without these, facial variations cause gaps, potentially making AM masks ineffective for respiratory protection.
Area of Science:
- Biomedical Engineering
- Materials Science
- Computational Mechanics
Background:
- The COVID-19 pandemic highlighted shortages of respiratory protection devices.
- Additive manufacturing (AM) face masks were rapidly developed, but their effectiveness was questioned due to limited performance evaluation.
- A need exists for reliable methods to assess the fit of AM-derived protective equipment.
Purpose of the Study:
- To introduce a novel computational methodology for evaluating the fit of additive manufacturing face masks.
- To assess the impact of design modifications, such as foam gaskets and variable sizing, on mask fit.
- To establish best practices for designing effective AM face masks.
Main Methods:
- Utilized finite element-based numerical simulations to virtually don AM face masks onto a standard digital headform.
- Extracted contour plots to visualize contact areas and quantify leakage through gaps between the mask and the headform.
- Analyzed the influence of foam gaskets and different mask sizes on the overall fit and leakage surface area.
Main Results:
- The simulation methodology effectively characterized the fit of AM mask frames, identifying critical areas of leakage.
- Appropriate sizing and the inclusion of a foam gasket significantly improved mask fit by reducing gaps.
- Rigid AM materials, without adjustments for facial morphology, led to substantial gaps and poor adaptability.
Conclusions:
- Additive manufacturing face masks can achieve adequate fit, crucial for respiratory protection, with careful consideration of sizing and sealing.
- The proposed simulation methodology provides a valuable tool for the functional performance evaluation of AM protective devices.
- Design strategies incorporating user-specific sizing and adaptive sealing elements are recommended for optimizing AM face mask efficacy.
