Computational Modelling of Gas-Particle Flows with Different Particle Morphology in the Human Nasal Cavity

Abstract

This paper summarises current studies related to numerical gas-particle flows in the human nasal cavity. Of interest are the numerical modelling requirements to consider the effects of particle morphology for a variety of particle shapes and sizes such as very small particles sizes (nanoparticles), elongated shapes (asbestos fibres), rough shapes (pollen), and porous light density particles (drug particles) are considered. It was shown that important physical phenomena needed to be addressed for different particle characteristics. This included the Brownian diffusion for submicron particles. Computational results for the nasal capture efficiency for nano-particles and various breathing rates in the laminar regime were found to correlate well with the ratio of particle diffusivity to the breathing rate. For micron particles, particle inertia is the most significant property and the need to use sufficient drag laws is important. Drag correlations for fibrous and rough surfaced particles were investigated to enable particle tracking. Based on the simulated results, semi-empirical correlations for particle deposition were fitted in terms of Peclet number and inertial parameter for nanoparticles and micron particles respectively.