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10.1111/ina.12908

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suck abstract from ncbi


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pmid34297885      Indoor+Air 2021 ; 31 (6): 1896-1912
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  • Variability in expiratory trajectory angles during consonant production by one human subject and from a physical mouth model: Application to respiratory droplet emission #MMPMID34297885
  • Ahmed T; Wendling HE; Mofakham AA; Ahmadi G; Helenbrook BT; Ferro AR; Brown DM; Erath BD
  • Indoor Air 2021[Nov]; 31 (6): 1896-1912 PMID34297885show ga
  • The COVID-19 pandemic has highlighted the need to improve understanding of droplet transport during expiratory emissions. While historical emphasis has been placed on violent events such as coughing and sneezing, the recognition of asymptomatic and presymptomatic spread has identified the need to consider other modalities, such as speaking. Accurate prediction of infection risk produced by speaking requires knowledge of both the droplet size distributions that are produced, as well as the expiratory flow fields that transport the droplets into the surroundings. This work demonstrates that the expiratory flow field produced by consonant productions is highly unsteady, exhibiting extremely broad inter- and intra-consonant variability, with mean ejection angles varying from approximately +30 degrees to -30 degrees . Furthermore, implementation of a physical mouth model to quantify the expiratory flow fields for fricative pronunciation of [f] and [theta] demonstrates that flow velocities at the lips are higher than previously predicted, reaching 20-30 m/s, and that the resultant trajectories are unstable. Because both large and small droplet transport are directly influenced by the magnitude and trajectory of the expirated air stream, these findings indicate that prior investigations of the flow dynamics during speech have largely underestimated the fluid penetration distances that can be achieved for particular consonant utterances.
  • |*Aerosols[MESH]
  • |*Air Pollution, Indoor[MESH]
  • |COVID-19[MESH]
  • |Humans[MESH]
  • |Mouth/*physiology[MESH]
  • |Research Subjects[MESH]
  • |SARS-CoV-2[MESH]


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