Visualizing flow partitioning in a model of the upper human lung airways

Area of Science:

• Fluid dynamics
• Biomedical engineering
• Respiratory physiology

Background:

• Understanding airflow dynamics in the human upper airway is crucial for respiratory health.
• High-frequency oscillatory ventilation (HFOV) is a clinical technique requiring detailed knowledge of airway fluid mechanics.
• Previous studies have not fully elucidated flow partitioning and particle dispersion under HFOV conditions.

Purpose of the Study:

• To investigate convective fluid transport and particle dispersion in a transparent model of the human tracheobronchial tree.
• To analyze flow partitioning within a six-generation branching network under simulated HFOV conditions.
• To determine the influence of varying Reynolds and Womersley numbers on airflow patterns and particle dispersion.

Main Methods:

• Utilized a transparent model of the human tracheobronchial tree.
• Simulated oscillatory flow at Reynolds numbers (400–2600) and Womersley numbers (5.5–12.3).
• Employed advection of neutrally buoyant tracer particles visualized by high-speed camera and light pulses to map flow and dispersion.

Main Results:

• Observed distinct flow partitioning characteristics across different Womersley and Reynolds numbers.
• Quantified particle dispersion patterns within the bifurcating airway network.
• Demonstrated that flow partitioning is sensitive to the tested range of airflow parameters.

Conclusions:

• Convective transport and particle dispersion in the upper airways are significantly influenced by airflow parameters (Reynolds and Womersley numbers).
• The findings provide insights into the complex fluid mechanics of high-frequency oscillatory ventilation.
• This research contributes to a better understanding of aerosol delivery and gas exchange in the lungs during HFOV.