Characterization of droplet clusters in a turbulent multiphase gas cloud using a model cough simulator

This study aims to investigate the transport of droplets ejected from an artificial cough simulator, which releases a turbulent puff of droplets into the surrounding air, closely resembling the human coughing process. The focus is on understanding droplet clustering within the multiphase gas cloud a...

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Published inPhysics of fluids (1994) Vol. 36; no. 11
Main Authors Vishwakarma, Ashish Kumar, Sahu, Srikrishna
Format Journal Article
LanguageEnglish
Published Melville American Institute of Physics 01.11.2024
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ISSN1070-6631
1089-7666
DOI10.1063/5.0233820

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Abstract This study aims to investigate the transport of droplets ejected from an artificial cough simulator, which releases a turbulent puff of droplets into the surrounding air, closely resembling the human coughing process. The focus is on understanding droplet clustering within the multiphase gas cloud across various operating conditions that emulate the wide variation in the spray characteristics in actual human subjects owing to infection severity, age, and gender. Time-resolved particle image velocimetry (PIV) technique was employed to measure the velocity of both droplet and gas phases. It also facilitates the identification and characterization of droplet clusters through Voronoi analysis of the PIV images. The area and length scale of individual droplet clusters were measured, and the degree of droplet clustering was quantified using the clustering index and relative droplet number density within the clusters. Additionally, the interferometric laser imaging for droplet sizing technique was utilized for planar measurement of individual droplet sizes. The range of Stokes number indicated partial to poor response of the droplets to the turbulent eddies. The results reported, for the first time, the presence of droplet clusters in the simulated coughing process. The wide spectrum of cluster size and self-similar evolution of droplet clusters unveil a multi-scale clustering phenomenon, shedding light on the intricate dynamics of the respiratory droplet dispersion process. The study comprehensively investigates the role of injection pressure on droplet clustering and the spatial development of the clusters, revealing some interesting findings, which are discussed.
AbstractList This study aims to investigate the transport of droplets ejected from an artificial cough simulator, which releases a turbulent puff of droplets into the surrounding air, closely resembling the human coughing process. The focus is on understanding droplet clustering within the multiphase gas cloud across various operating conditions that emulate the wide variation in the spray characteristics in actual human subjects owing to infection severity, age, and gender. Time-resolved particle image velocimetry (PIV) technique was employed to measure the velocity of both droplet and gas phases. It also facilitates the identification and characterization of droplet clusters through Voronoi analysis of the PIV images. The area and length scale of individual droplet clusters were measured, and the degree of droplet clustering was quantified using the clustering index and relative droplet number density within the clusters. Additionally, the interferometric laser imaging for droplet sizing technique was utilized for planar measurement of individual droplet sizes. The range of Stokes number indicated partial to poor response of the droplets to the turbulent eddies. The results reported, for the first time, the presence of droplet clusters in the simulated coughing process. The wide spectrum of cluster size and self-similar evolution of droplet clusters unveil a multi-scale clustering phenomenon, shedding light on the intricate dynamics of the respiratory droplet dispersion process. The study comprehensively investigates the role of injection pressure on droplet clustering and the spatial development of the clusters, revealing some interesting findings, which are discussed.
Author Vishwakarma, Ashish Kumar
Sahu, Srikrishna
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  givenname: Srikrishna
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  organization: Thermodynamics and Combustion Engineering Laboratory, Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai, India
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Snippet This study aims to investigate the transport of droplets ejected from an artificial cough simulator, which releases a turbulent puff of droplets into the...
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SubjectTerms Cluster analysis
Clustering
Cough
Droplets
Multiphase
Particle image velocimetry
Self-similarity
Spray characteristics
Stokes number
Vapor phases
Velocity measurement
Title Characterization of droplet clusters in a turbulent multiphase gas cloud using a model cough simulator
URI http://dx.doi.org/10.1063/5.0233820
https://www.proquest.com/docview/3124169591
Volume 36
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