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For face profiles that don't follow the norm, the use of respirators can lead to a false sense of security due to air leakage or a contamination threat. The National Institute of Science and Technology has been engaged in a multi-year program to improve the safety and effectiveness of full-face respirator masks.
To meet some impending deadlines on this project, Predictive Engineering was competitively awarded an investigative project to study the fit and function of an industry standard respirator mask.
A key finding of this work was that the modeling of human skin is best represented as a flexible bag of viscous fluid and not as a semi-elastic solid as has been done in prior work external to NIST.
CFD studies also indicated that air flow within the respirator mask is not optimized and could be improved with some minor geometric changes.
These and other findings are scheduled for publication under the NIST banner with a gracious co-authorship to Predictive Engineering for meeting project goals on time and on target.
Model Details
The project involved the complete analysis of the fitting process between a respirator mask and a human head. The respirator seal geometry was provided as IGES data generated from laser scanning process over the original respirator. Head geometry was provided in a similar format.
Femap was able to parse the skins together and create a clean manifold skin that facilitated a quad-dominate mesh for the respirator and likewise a smooth tet mesh for the head.
Silicone rubber respirator seal and human skin model.
This model was then submitted to LS-DYNA for a complete fit and contact analysis. The mast was actually pulled against the face and allowed to seal. Seal pressures were then generated.
LS-DYNA model of mask fit pressures.
For functional analysis, a transient CFD analysis was performed using CFdesign. This was quite tricky since the original geometry was not quite representative of the flow passage within the respirator. With some cleanup help from Femap, a clean model was then submitted to CFdesign. It was impressive how well CFdesign handled the transient flow conditions for inhalation and exhalation through the use of ramped flow-rate curves. CFD results were checked for convergence with the mass balance error under 1%.
Inhalation model at the working respiration rate.
About Predictive Engineering
Led by CEO and owner George Laird, Predictive Engineering has executed some 750 projects over the last six years, working with clients’ engineering teams to deliver the best possible structural and thermal/fluid designs.
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