Exploring the role of nasal hair in inhaled airflow and coarse dust particle dynamics in a nasal cavity: A CFD-DEM study

Abstract

This study presents a novel coupled computational fluid dynamics-discrete element method (CFD-DEM) model for simulating airflow and inhaled particle dynamics in the nasal cavity, considering the fluid-structure interactions between nasal hair and airflow, which are often overlooked in existing CFD simulations. The CFD-DEM model, based on a virtual nasal cavity geometry, represents nasal hairs as flexible fibers implanted on the inner wall of the nasal cavity. Inhaled air-particle transport dynamics were simulated in the presence of nasal hairs with three different diameters (40, 95, and 120 μm), and the results were compared with simulations without nasal hairs. Polydisperse particles with diameters ranging from 5 to 15 μm, aligning with global coarse dust statistics, were inhaled at flow rates between 216 mL/s and 630 mL/s, representing human nose breathing conditions from rest to exercise. The CFD-DEM simulation results indicate that the differences in deposition fraction predictions between cases with and without nasal hairs exceed 20% for particle size ranges corresponding to impaction parameter values between 3E+3 and 2E+4 μm2cm3/s. This emphasizes the importance of accounting for nasal hair interactions in accurately simulating inhaled particle transport dynamics within the nasal cavity. Thinner nasal hairs, more flexible than thicker ones, lead to more significant deformation and allow more particles to penetrate the nasal vestibule without being trapped. Additionally, thinner hairs occupy a smaller cross-section area in the nasal vestibule, resulting in lower filtration capability due to decreased particle deposition from interception and inertial impaction. Thicker nasal hairs trap more coarse dust particles (> 5 μm) effectively than thinner nasal hairs. Moreover, as the nasal hair diameter increases, particle deposition on the nasal cavity wall decreases. Nasal hairs demonstrate higher efficiency in trapping smaller particles. In conclusion, the CFD-DEM model, capable of modeling nasal hair motion, can serve as a next-generation in silico tool for investigating biofluid dynamics in the nasal cavity.