High frequency oscillatory ventilation (HFOV) relies on low tidal volumes cycled at supraphysiologic rates, producing fundamentally different mechanisms for gas transport and exchange compared to conventional mechanical ventilation. Despite the appeal of using low tidal volumes to mitigate the risks of ventilator- induced lung injury (VILI), HFOV does not improve mortality in most clinical applications. One possible explanation for this is that HFOV distributes flows throughout the lung in a non-uniform and frequency-dependent manner, especially in the presence of mechanical heterogeneity. This thesis is a systematic investigation of the relationship between carbon dioxide elimination and frequency content during oscillatory ventilation, with emphasis on the frequency- dependent effects of mechanical heterogeneity and various gas transport mechanisms. A computational model consisting of an anatomically-structured airway network was used to simulate ventilation distribution and gas exchange in a canine lung. These simulations were validated against theoretical predictions and experimental data for eucapnic oscillatory ventilation. The model was also used to assess the impact of mechanical heterogeneity on ventilation distribution and gas transport. Simulations demonstrated a critical transition at the resonant frequency, above which the ventilation patterns became spatially clustered and frequency-dependent. Finally, the model demonstrated that pairs of oscillatory frequencies could yield eucapnic conditions with less potential for VILI compared to traditional single frequency HFOV. These results illustrate the importance of frequency selection in managing the distribution of ventilation and gas transport in the heterogeneous lung, and suggest that the frequency content in oscillatory waveforms may be optimized to achieve eucapnic gas exchange using less injurious ventilation. / 2017-10-27T00:00:00Z