Computational fluid dynamics of particles’ transport in the airways (Vuorinen et al., 2025)
Purpose: Our purpose was to model the transport and fate of respiratory particles in the vocal tract during phonation and to determine the size of particles that can be emitted if generated at the level of glottis or below. The COVID-19 pandemic and associated discussion on airborne transmission has led to a need to understand particle emission during respiratory activities and its mechanisms. Computational fluid dynamics (CFD) simulations can model particle transport inside the airways, as in vivo measurements remain challenging.
Method: CFD (large eddy) simulations were used to analyze airflow patterns in the vocal tract and the motion of particles (1–100 μm) introduced from the level of glottis. The effect of airflow velocity was evaluated.
Results: In the model, the upper airway filtered the large particles, allowing only particles < 10 μm to exit the mouth. The cutoff size for filtration depends on airflow velocity and Stokes number of particles, which describes a particle’s tendency to follow the flow. The results indicate that the cutoff size decreases when the flow rate increases.
Conclusions: We demonstrated that the largest particles (> 5–10 μm) formed below the pharynx may adhere to airway walls due to the complex anatomy of the vocal tract. We propose that the primary deposition mechanism is the inability of these particles to change direction at locations where the flow turns. The results therefore suggest that infections in lower airways may transmit primarily via small particles. This should be considered when planning suitable protective measures.
Supplemental Material S1. Video showing CFD simulation of the airflow, particle transport, and deposition in the vocal tract.
Vuorinen, V., Siddiqui, W., Laurila, E., Izbassarov, D., Korhonen, M., Sanmark, E., Geneid, A., Oksanen, L.-M., & Tuhkuri Matvejeff, A. (2025). Computational fluid dynamics modeling of particle transport from the vocal folds to the oral cavity. Journal of Speech, Language, and Hearing Research, 68(7), 3107–3118. https://doi.org/10.1044/2025_JSLHR-24-00896
