Literature Database Entry
gulec2022characterization
Fatih Güleç, Falko Dressler and Andrew W. Eckford, "Characterization of Airborne Pathogen Transmission in Turbulent Molecular Communication Channels," Proceedings of IEEE Global Communications Conference (GLOBECOM 2022), Rio de Janeiro, Brazil, December 2022, pp. 4523–4528.
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 − ε 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 multi-modal distributions as a weighted sum of normal and Weibull distributions.
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Fatih Güleç
Falko Dressler
Andrew W. Eckford
BibTeX reference
@inproceedings{gulec2022characterization,
author = {G{\"{u}}le{\c{c}}, Fatih and Dressler, Falko and Eckford, Andrew W.},
doi = {10.1109/GLOBECOM48099.2022.10001692},
title = {{Characterization of Airborne Pathogen Transmission in Turbulent Molecular Communication Channels}},
pages = {4523--4528},
publisher = {IEEE},
isbn = {978-1-66543-540-6},
address = {Rio de Janeiro, Brazil},
booktitle = {IEEE Global Communications Conference (GLOBECOM 2022)},
month = {12},
year = {2022},
}
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