Computational Fluid Dynamics Modeling of Particle Transport From the Vocal Folds to the Oral Cavity

Area of Science:

• Aerosol science
• Biomedical engineering
• Respiratory physiology

Background:

• Understanding airborne transmission of respiratory infections is crucial, especially post-COVID-19.
• In vivo measurements of particle transport in the vocal tract are challenging.
• Computational fluid dynamics (CFD) offers a viable method for modeling these processes.

Purpose of the Study:

• To model the transport and fate of respiratory particles within the vocal tract during phonation.
• To determine the size of particles that can be emitted when generated at or below the glottis.
• To investigate the mechanisms of particle emission and filtration during speech.

Main Methods:

• Employed large eddy Computational Fluid Dynamics (CFD) simulations.
• Analyzed airflow patterns and particle motion (1-100 μm) within a vocal tract model.
• Evaluated the effect of airflow velocity on particle transport and deposition.

Main Results:

• The upper airway acts as a filter, preventing particles larger than 10 μm from exiting the mouth.
• Filtration cutoff size is dependent on airflow velocity and particle Stokes number.
• Increased flow rate leads to a decrease in the cutoff size for particle emission.

Conclusions:

• Particles >5-10 μm generated below the pharynx may deposit on airway walls due to complex vocal tract anatomy and flow dynamics.
• Particle deposition is primarily driven by the inability of larger particles to follow rapid changes in airflow direction.
• Findings suggest lower airway infections are mainly transmitted via smaller particles, informing protective measure strategies.