Computational fluid dynamics (CFD) simulations were performed to predict the air flow in the human lung during cyclic breathing. The study employed a morphologically complex computational geometry generated using a combination of patient-specific CT-scan data for the extrathoracic and upper airway regions and a representative branching geometry for the lower airways that is available in the open literature. The geometry extended throughout the entire conducting zone and includes 16 partially resolved airway generations. For each generation beyond the third, only a fraction of the airway branches were retained, resulting in truncated flow outlets (for inspiratory flow) in generations 414. The inhalation and exhalation air flow boundary conditions were prescribed based on a physiologically realistic ventilation pattern, which was obtained using a whole-body model of human physiology. The flow was driven by specifying time-varying volumetric flowrates applied at each of the distal boundaries, while the oral boundary was maintained at constant (atmospheric) pressure. The study investigated the effectiveness of three different mass flow distribution schemes to drive the air flow. It was found that prescribed mass flow distribution fractions based on the square of the airway cross-sectional area produced the best results in terms of a uniform distal pressure distribution, while all methods produced reasonable results in terms of mass flow distribution throughout the lung airway geometry.

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