École Nationale Supérieure de
Techniques Avancées

Résumé

In times of pandemic, such as the COVID-19 one, it becomes important to find efficient solutions and public health guidelines to reduce the virus transmission among the population. This transmission between individuals happens via infected airborne droplets, that are emitted during various respiratory events (e.g.coughing, sneezing, normal breathing). Face masks appear as a solution to limit the spread of the virus. In this project, we aim at assessing the filtration efficiency (as the percentage of captured particles) of a three-layer surgical mask, under various breathing conditions. Exploitable samples have been extracted from the X-ray reconstruction of the face mask, before being used in two successive simulations: a latticeBoltzmann algorithm solving the flow field in the samples, and a Lagrangian-Particle-Tracking-based simulation computing the trajectories and the capture of the droplets by the samples microstructures,using the solved flow data. The partial results obtained during the internship show that, as expected, the three layers of the mask perform differently, the middle one being the most efficient. Furthermore, it can be established that the mask presents a efficiency minimum for incident particles with an approximate 10−2µm diameter.