Computational Fluid Dynamics‐Based Optimization of Face Mask Filter Media Using Micro‐Computed Tomography Scans

Abstract

AbstractDuring the COVID‐19 pandemic, face masks have become an important protective measure for reducing the spread of potentially infectious aerosol particles emitted while speaking, coughing, or simply breathing. In this work, a voxel‐based numerical model obtained from micro‐computed tomography (microCT) scans of a medical mask was validated by comparing fractional filtration efficiency and net pressure loss to values measured at an in‐house mask test bench after discharging the mask in isopropanol. Varying mean fiber diameter, solid volume fraction, and thickness of the filter medium, parametric studies based on a digital twin of the mask sample were carried out. It is demonstrated that face masks can be designed where filtration efficiency, pressure drop, and material consumption is improved compared to the base case.