Abstract
Loose-fitting powered air-purifying respirators (PAPRs) are used in healthcare settings to reduce exposure to high-risk respiratory pathogens. Innovative computational fluid dynamics (CFD) models were developed for evaluating loose-fitting PAPR performance. However, the computational results of the CFD models have not been validated using actual experimental data.
Experimental testing to evaluate particle facepiece leakage was performed in a test laboratory using two models of loose-fitting PAPRs. Each model was mounted on a static (non-moving) advanced headform placed in a sodium chloride (NaCl) aerosol test chamber. The headform performed cyclic breathing via connection to a breathing machine. High-efficiency particulate air (HEPA)-filtered air was supplied directly to the PAPR facepiece using laboratory compressed supplied-air regulated with a mass-flow controller. One model was evaluated with six supplied-air flowrates from 50–215 L/min (Lpm) and the other model with six flowrates from 50–205 Lpm. Three different workrates (minute volumes) were evaluated: low (25 Lpm), moderate 46 (Lpm), and high 88 (Lpm). Manikin penetration factor (mPF) was calculated as the ratio of chamber particle concentration to the in-facepiece concentration.
Overall, data analyses indicated that the mPF results from the simulations were well correlated with the experimental laboratory data for all data combined (r = 0.88). For data at the three different workrates (high, moderate, low) for both models combined, the r-values were 0.96, 0.97, and 0.77, respectively. The CFD models of the two PAPR models were validated and may be utilized for further research.
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Bergman, M., Lei, Z., Xu, S., Strickland, K., Zhuang, Z. (2019). Validation of Computational Fluid Dynamics Models for Evaluating Loose-Fitting Powered Air-Purifying Respirators. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 819. Springer, Cham. https://doi.org/10.1007/978-3-319-96089-0_20
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