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A reduced-order model of face mask aerodynamics and aerosol filtration is introduced. This model incorporates existing empirical data on filtration efficiency for different types of face masks, as well as the size distribution of exhaled aerosol particles. By considering realistic peripheral gap profiles, our model estimates both the extent of peripheral leakage and the fitted filtration efficiency of face masks in terms of outward protection. Simulations employing realistic peripheral gap profiles reveal that, for surgical masks, 80% or more of the total exhaled airflow could leak through the mask periphery, even when the average peripheral gap measures only 0.65 mm. However, the majority of exhaled aerosol particles do not follow the flow path through the peripheral gaps but, instead, impact directly on the mask fabric. As a result, these face masks can filter out approximately 70% of the exhaled particles despite the significant peripheral leakage. To validate our model, we compare its predictions with experimental data, and we find a reasonable agreement in estimating the outward protection provided by surgical masks. This validation underscores the reliability of our model in assessing the efficacy of surgical masks. Moreover, leveraging the insights gained from our model, we explore the impact of mask usage on the transmission of respiratory viruses within communities. By considering various scenarios, we can assess the potential reduction in viral spread achieved through widespread mask adoption. 

Due to the COVID-19 pandemic, face masks have been used extensively in society. The effectiveness of face masks depends on their material, design, and fit. With much research being focused on quantifying the role of the material, the design and fit of masks have been an afterthought at most. Recent studies, on the other hand, have shown that the mask fit is a significant factor to consider when specifying the effectiveness of the face mask. Moreover, the fit is highly dependent on face topology. Differences in face types and anthropometrics lead to different face mask fit. Here, computational fluid dynamics simulations employing a novel model for porous membranes (i.e., masks) are used to study the leakage pattern of a cough through a face mask on different faces. The three faces studied (female, male, and child) are characteristic faces identified in a previous population study. The female face is observed to have the most leakage through the periphery of the mask, which results in the lowest fitted filtration efficiency of the three faces. The male and child faces had similar gap profiles, leakage and fitted filtration efficiencies. However, the flow of the three faces differs significantly. The effect of the porosity of the mask was also studied. While all faces showed the same general trend with changing porosity, the effect on the child’s face was more significant. 

The use of face masks by the general population during viral outbreaks such as the COVID-19 pandemic, although at times controversial, has been effective in slowing down the spread of the virus. The extent to which face masks mitigate the transmission is highly dependent on how well the mask fits each individual. The fit of simple cloth masks on the face, as well as the resulting perimeter leakage and face mask efficacy, are expected to be highly dependent on the type of mask and facial topology. However, this effect has, to date, not been adequately examined and quantified. Here, we propose a framework to study the efficacy of different mask designs based on a quasi-static mechanical model of the deployment of face masks onto a wide range of faces. To illustrate the capabilities of the proposed framework, we explore a simple rectangular cloth mask on a large virtual population of subjects generated from a 3D morphable face model. The effect of weight, age, gender, and height on the mask fit is studied. The Centers for Disease Control and Prevention (CDC) recommended homemade cloth mask design was used as a basis for comparison and was found not to be the most effective design for all subjects. We highlight the importance of designing masks accounting for the widely varying population of faces. Metrics based on aerodynamic principles were used to determine that thin, feminine, and young faces were shown to benefit from mask sizes smaller than that recommended by the CDC. Besides mask size, side-edge tuck-in, or pleating, of the masks as a design parameter was also studied and found to have the potential to cause a larger localized gap opening. 

Recent studies have shown that the effectiveness of the face masks depends not only on the mask material but also on their fit on faces. The mask porosity and fit dictate the amount of filtered flow and perimeter leakage. Lower porosity is usually associated with better filtration; however, lower porosity results in higher perimeter leakage. The resulting leakage jets generated from different types of faces and different mask porosities are of particular interest. Direct numerical simulations of the flow dynamics of respiratory events while wearing a face mask can be used to quantify the distribution of the perimeter leaks. Here, we present a novel model for porous membranes (i.e., masks) and use it to study the leakage pattern of a fabric face mask on a realistic face obtained from a population study. The reduction in perimeter leakage with higher porosities indicates that there would be an optimal porosity such that the total leakage and maximum leakage velocities are reduced. The current model can be used to inform the quantification of face mask effectiveness and guide future mask designs that reduce or redirect the leakage jets to limit the dispersion of respiratory aerosols.