Abstract
Prematurely born infants are at risk of developing respiratory distress syndrome (RDS)due to a deficiency of pulmonary surfactant. Without this surface tension reducing molecule, large pressure gradients in the lung can lead to atelectasis and increase mortality risk. Medical practitioners treat RDS with surfactant replacement therapy (SRT), a procedure which reintroduces exogenous surfactant into the airway. However, SRT has a 35% non-response rate, largely due to the challenges of delivering the surfactant uniformly, and reaching the distal regions of the lung. Current research has focused on understanding the physics of Newtonian surfactant delivery, specifically how the plug propagates along the airway, deposits its mass onto the airway wall, and splits at each airway bifurcation. However, in practice, many of the surfactants used exhibit non-Newtonian shear thinning behavior. Additionally, the mucus in the lung forms a bilayer of periciliary fluid, composed of mostly Newtonian fluid. This complexity introduces additional challenges for computational simulations, as no established methods currently exist for simulating non-Newtonian liquid interactions, with Newtonian liquid, and gas. This thesis addresses the current gap in research by developing a novel numerical method using the volume-of-fluid (VOF) approach. This method enables computational simulations that accurately capture interactions between a non-Newtonian shear-thinning liquid, a Newtonian liquid, and gas in the presence of a rigid body. To validate its accuracy, semi-analytical solutions are derived for multiphase Poiseuille ow of non-Newtonian and Newtonian fluids. Additionally, numerical simulations are conducted for canonical cases, such as bubbles rising in shear-thinning fluids. Finally, the numerical method is applied to simulate non-Newtonian surfactant plugs propagating through straight capillary tubes and a bifurcating airway model. The interplay between non-Newtonian plugs and the pre-existing film is analyzed, highlighting its potential implications for improving SRT.