Deep in the Lung: Lagrangian Transport in Alveolar Flows

This thesis investigates the transport and deposition of nanoparticles in the human lung, a primary target for atmospheric particulate matter. A realistic normal human breathing waveform is used to simulate airflow over a simplified 3D computational alveolus. An efficient interpolation method is developed to integrate particle trajectories, generating a continuous velocity field from discrete data. The results are compared to the widely reported sinusoidal pressure-driven model. While both breathing patterns show similar alveolar emptying rates, they differ in airflow distribution and particle deposition. These findings highlight the importance of breathing waveforms in determining particle deposition locations, with implications for lung health and aerosolized drug delivery.