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Review
. 2020 Nov 1;32(11):111301.
doi: 10.1063/5.0029767.

The perspective of fluid flow behavior of respiratory droplets and aerosols through the facemasks in context of SARS-CoV-2

Sanjay Kumar  1 , Heow Pueh Lee  1
Affiliations
Review

The perspective of fluid flow behavior of respiratory droplets and aerosols through the facemasks in context of SARS-CoV-2

Sanjay Kumar et al. Phys Fluids (1994). .

Abstract

In the unfortunate event of the current ongoing pandemic COVID-19, where vaccination development is still in the trial phase, several preventive control measures such as social distancing, hand-hygiene, and personal protective equipment have been recommended by health professionals and organizations. Among them, the safe wearing of facemasks has played a vital role in reducing the likelihood and severity of infectious respiratory disease transmission. The reported research in facemasks has covered many of their material types, fabrication techniques, mechanism characterization, and application aspects. However, in more recent times, the focus has shifted toward the theoretical investigations of fluid flow mechanisms involved in the virus-laden particles' prevention by using facemasks. This exciting research domain aims to address the complex fluid transport that led to designing a facemask with a better performance. This Review discusses the recent updates on fluid flow dynamics through the facemasks. Key design aspects such as thermal comfort and flow resistance are discussed. Furthermore, the recent progress in the investigations on the efficacy of facemasks for the prevention of COVID-19 spread and the impact of wearing facemasks is presented.

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Figures

FIG. 1.
FIG. 1.
(a) The 3D schematics of the ventilator mask integrated with the volunteer’s face. (b) Distribution of the averaged residual CO2 concentration inside the ventilator mask varying with time during a complete respiratory cycle. Reproduced with permission from Zhang et al., “Individualized design of the ventilator mask based on the residual concentration of CO2,” Comput. Model. Eng. Sci. 117, 157 (2018). Copyright 2018 Author(s) licensed under a Creative Commons Attribution 4.0 License. (c) The surface of the airway model at six instants through the breathing maneuver. The model was extended from the mask worn by the wearer. (d) The resistance to airflow through the breath. The colored lines represent the resistance (left axis) through each of the regions between the planes shown in the inset (top left). The solid lines show the resistance in the moving wall simulation, while the dashed lines show the resistance in the same regions in the static geometry. The black curve shows the flow rate throughout the breath (right axis). Reproduced with permission from Bates et al., “Assessing the relationship between movement and airflow in the upper airway using computational fluid dynamics with motion determined from magnetic resonance imaging,” Clin. Biomech. 66, 88 (2019). Copyright 2019 Elsevier Ltd.
FIG. 2.
FIG. 2.
(a) Schematic geometry for airflow through a generic hemi-spherical facemask with gap height Hg and gap length Lg over a width Bg along its perimeter. ut, um, and ug denote average airflow velocities through nose cross-sectional area St, mask filter surface Sm, and gap cross-sectional area Sg. pm and pa signify the pressure inside and outside (atmospheric) of the mask. (b) 3D representation of facemasks with wearer showing the possible region for leakage. Reproduced with permission from R. Perić and M. Perić, arXiv:2005.08800 (2020). Copyright 2020 arXiv.org.
FIG. 3.
FIG. 3.
[(a) and (b)] Schematics of the proposed hybrid facemask (nanofibers/nanoPE) and its photograph. (c) The SEM images show the condition of nylon-6 fibers before and after filtering the particulate matter (PM). [(d) and (e)] The removal efficiency of the fiber/nanoPE facemasks compared to two commercial masks, and their pressure drop spectra as a function of the wind velocity. Reproduced with permission from Yang et al., “Thermal management in nanofiber-based face mask,” Nano Lett. 17, 3506 (2017). Copyright 2017 American Chemical Society.
FIG. 4.
FIG. 4.
(a) Schematic illustration of the possible filtration mechanism of the hybrid cloth masks. In addition, the plot shows the filtration efficiencies of a surgical mask and hybrid fabric cotton/silk with (dashed) and without a gap (solid). The gap used was ∼1% of the active mask surface area. Reprinted with permission from Konda et al., “Aerosol filtration efficiency of common fabrics used in respiratory cloth masks,” ACS Nano 14, 6339 (2020). Copyright 2020 American Chemical Society. (b) Performance comparison between the medical masks and the three-layer cotton mask. Reproduced with permission from Ho et al., “Medical mask versus cotton mask for preventing respiratory droplet transmission in micro environments,” Sci. Total Environ. 735, 139510 (2020). Copyright 2020 Elsevier B.V. (c) Photographs of the facemasks under investigation: (1) three-layer surgical mask, (2) N95 mask with a exhalation valve “Valved N95,” (3) knitted mask, (4) double-layer polypropylene apron mask “Polyprop,” (5) cotton–polypropylene–cotton mask “Poly/cotton,” (6) single layer Maxima AT mask “MaxAT,” (7) double-layer cotton-pleated style mask “Cotton2,” (8) double-layer cotton mask–Olson style mask “Cotton4,” (9) double-layer cotton-pleated style mask “Cotton3,” (10) single-layer cotton-pleated style mask “Cotton1,” (11) gaiter type neck fleece “Fleece,” (12) double-layer bandana “Bandana,” (13) single-layer cotton-pleated style mask “Cotton5,” and (14) N95 mask no exhalation valve fitted “Fitted N95.” (d) Relative droplet transmission through the corresponding facemasks. (e) Schematic of the experimental optical setup. Reproduced with permission from Fischer et al., “Low-cost measurement of face mask efficacy for filtering expelled droplets during speech,” Sci. Adv. 6, eabd3083 (2020). Copyright 2015 Author(s), licensed under a Creative Commons Attribution 4.0 License.
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