Characterization of Airborne Pathogen Transmission in Turbulent Molecular Communication Channels
2022 IEEE Global Communications Conference, GLOBECOM 2022
; : 4523-4528, 2022.
Article
in English
| Scopus | ID: covidwho-2230586
ABSTRACT
Airborne pathogen transmission mechanisms play a key role in the spread of infectious diseases such as COVID-19. In this work, we propose a computational fluid dynamics (CFD) approach to model and statistically characterize airborne pathogen transmission via pathogen-laden particles in turbulent channels from a molecular communication viewpoint. To this end, turbulent flows induced by coughing and the turbulent dispersion of droplets and aerosols are modeled by using Reynolds-averaged Navier-Stokes equations coupled with realizable k-epsilon model and the discrete random walk model, respectively. Via the simulations realized by a CFD simulator, statistical data for the number of received particles are obtained. These data are post-processed to obtain the statistical characterization of the turbulent effect in the reception and to derive the probability of infection. Our results reveal that the turbulence has an irregular effect on the probability of infection which shows itself by the multimodal distributions as a weighted sum of normal and Weibull distributions. © 2022 IEEE.
Aerosols; Computational fluid dynamics; Navier Stokes equations; Pathogens; Transmissions; Airborne pathogens; Communications channels; Flow induced; Fluid-dynamics approach; Infectious disease; Molecular communication; Reynolds Averaged Navier-Stokes Equations; Transmission mechanisms; Turbulent channels; Turbulent dispersion; Weibull distribution
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Randomized controlled trials
Language:
English
Journal:
2022 IEEE Global Communications Conference, GLOBECOM 2022
Year:
2022
Document Type:
Article
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