Abstract
During the onging pandemic of COVID-19, there are numerous asymptomatic patients who are infectious. The exhaled droplets from their daily respiratory activities like breathing or speaking can be the sources of airborne disease transmission of COVID-19. The understanding of the airflow dynamics of these respiratory activities may be helpful to develop effective measures to prevent and control the spread of the disease. In this study, the exhaled flows from human breathing and vocalization of specific syllables are characterized using particle image velocimetry (PIV) and smoke visualization. The exhaled flow generated by ten phonemes including vowels, fricatives, affricates, plosives and nasals as well as mouth breathing are studied. The dynamic developments of the airflow processes are described by a series of parameters, including peak velocity, peak velocity time, duration time, propagation velocity and distance. Results show that vocalization of affricates and plosives as well as mouth breathing tend to have higher peak velocities and propagation distances. The evolutions of exhaled flows generated from these respiratory processes are found to have different jet structures, which are related to the stroke ratio (L/D). The flow field of a small L/D only has a pair of dominant vortices. Whereas that of a large L/D presents both a pair of dominant vortex ring and a trailing jet. Certain phoneme (e.g., /t/) is found to display a two-stage jet similar to a cough with the starting jet and an interrupted jet. The characterization of human exhaled flow of this study may be helpful to provide basis of CFD simulations and a better understanding of the spread of airborne diseases from human breathing.
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