Modelling Analysis of Face Shield Effectiveness Against COVID-19 Transmission

Abstract

The ongoing COVID-19 pandemic necessitates effective protective measures to mitigate virus transmission. This study employed Computational Fluid Dynamics (CFD) to evaluate the efficacy of two face shield models in blocking COVID-19 transmission under three conditions: normal speech, coughing, and sneezing. One model replicates a common commercial product, and the other introduces an innovative design. A simplified human model with dimensions of 760 × 300 mm and a mouth air inlet area of 360 mm² was used for the simulation. Two types of face shields were modelled: one with a simple curved structure (Model 1) and another with a rectangular structure providing a side cover (Model 2). The computational domain was defined with dimensions of 3.5 m x 2.8 m x 2.3 m, and simulations were conducted using the finite volume method with ANSYS Meshing and Fluent for solver preference. The governing equations for the incompressible flow were applied. The simulations revealed that both face shields effectively blocked the direct airflow to the face across all conditions (speech, coughing, and sneezing). However, the structure of the face shields significantly alters the airflow patterns. Model 2, with its rectangular structure, provided better coverage and directed the airflow away from critical areas. Despite their effectiveness in blocking direct contact with airborne particles, face shields alone do not provide sufficient protection against virus transmission, especially for finer aerosol particles. Face shields can obstruct direct airflow but are inadequate as standalone protective measures against COVID-19 transmission. Therefore, the combined use of face shields and face masks is recommended for enhanced safety.