Effect of face shield design on the prevention of sneeze droplet inhalation

Abstract

A flow simulation was performed for face shields to investigate whether varying a shield's edge shape could prevent droplets from entering the shield. Face shields with two types of edge shapes were used. The “Type I” shield had small plates mounted on the top and bottom edges of the shield to physically inhibit the sneeze inflow. The “Type II” shield had small brims sticking forward from the shield surface and small plates sticking upward and downward at the top and bottom edges to inhibit the entrainment flow produced by the vortex ring using sneeze flow. We confirmed that the flow characteristics around a face shield can be controlled using the shield's edge shape. In Type I, the entraining flow inside the shield was inhibited by the mounted small plate at the bottom edge, ensuring the inhibiting effect, but not at the top edge. In Type II, the entrained flow inside the shield was inhibited by the mounted brim and small plate at the top edge, ensuring the inhibiting effect, but not at the bottom edge. The effects of the Type II design parameters on the flow characteristics around the face shield were examined. The results indicate that at the top edge, increasing the length of the brim and not mounting the small plate at an incline from the shield surface improves the inhibition effect. At the bottom edge, shortening the length of the brim and mounting the small plate at an incline from the shield surface improves the inhibition effect.

Particle leakage through the exhalation valve on a face mask under flow conditions mimicking human breathing: A critical assessment

“…While the detailed profiles may different among each other, the transition rate between exhalation and inhalation is an important factor to determine the unsteady flow structures. For the present cases, the transition rate normalized by the maximum flow rate ( Q ) is approximately 3.0 s −1 ( L/min), which is in the same order of previous studies; it was 1.8 s −1 for Q = 24 L/min ( Gupta et al , 2010 ) and 3.1 s −1 for Q = 60 L/min ( Akagi et al , 2021 ). While the present transition occurs faster than the normal breathing condition, it is reasonable considering that the phase conversion occurs faster as the respiratory flow rate increases.…”

“…Here, we measure the airflow fields and accompanying particle migration as the transition from the ejection to suction occurs, in which the duration of each is 2.0 s. Figure 14 shows the temporal variation of the airflow rate measured for each Q , which shows a relatively sharp phase transition. Previous studies related to face mask or virus transmission used the modeled human respiratory flow in various ways, mostly based on the results from Gupta et al (2010) , such as a sine wave ( Khosronejad et al , 2021 ), partially linear profile ( Lei et al , 2013 ; Zhang et al , 2016 ; Akagi et al , 2021 ), and periodic square wave ( Dbouk and Drikakis, 2020a ). While the detailed profiles may different among each other, the transition rate between exhalation and inhalation is an important factor to determine the unsteady flow structures.…”

Development and evaluation of a fluidic facemask for airborne transmission mitigation

“…Furthermore, they are ungainly and tend to become contaminated with exhaled droplets or due to contact with unsterilized surfaces after a short time [22] . Recent research has shown, however, that coating the shields with silica nanoparticles can render them potentially more efficacious [23] , and modifications to the edges of the shields can improve their effectiveness [24] . Despite these essential improvements and studies, there remains an urgent need for a comfortable facemask that does not inhibit breathing and has no negative impact on facial recognition or verbal communication.…”

Numerical modeling of sneeze airflow and its validation with an experimental dataset

“…Thus, an attempt was made to reproduce the transient jet airflow of a cough by exploring the boundary conditions of the CFD simulations from the results of the PIV experiment 10 . Several studies tried to investigate the effect of face shields on infectious particles generated by sneezing has been studied 25–27 . Ugarte–Anero assumed that the sneeze airflow had a constant speed of 16 m/s for a duration of 0.4 s 25 .…”

“…10 Several studies tried to investigate the effect of face shields on infectious particles generated by sneezing has been studied. [25][26][27] Ugarte-Anero assumed that the sneeze airflow had a constant speed of 16 m/s for a duration of 0.4 s. 25 Akagi et al used the gamma probability distribution of coughing derived by Gupta et al for sneeze simulation. 26,27 Fontes et al assumed that the sneeze airflow had a maximum velocity of 50 m/s in the numerical simulation of particle dispersion.…”