TY - GEN
T1 - Simulation of droplet dispersion in COVID-19 type pandemics on Fugaku
AU - Bale, Rahul
AU - Li, Chung Gang
AU - Yamakawa, Masashi
AU - Iida, Akiyoshi
AU - Kurose, Ryoichi
AU - Tsubokura, Makoto
N1 - Funding Information:
This work was supported by JST CREST Grant Number JPMJCR20H7, Japan, and through the computing resources provided on the Fu-gaku supercomputer by the RIKEN Center for Computational Science and through the HPCI system research project (Project ID: hp200154).
Publisher Copyright:
© 2021 ACM.
PY - 2021/7/5
Y1 - 2021/7/5
N2 - Transmission of infectious respiratory diseases through airborne dispersion of viruses poses a great risk to public health. In several major diseases, one of the main modes of transmission is through respiratory droplets. Virus laden respiratory droplets and aerosols can be generated during coughing, sneezing and speaking. These droplets and aerosols can remain suspended in air and be transported by airflow posing a risk of infection in individuals who might come in contact with them. With this background, in this work, we present a numerical framework for simulation of dispersion of respiratory sputum droplets using implicit large-eddy simulations. A combination of discrete Lagrangian droplet model and fully compressible Navier-Stokes flow solver is employed in this study. The method is applied to analyze cases such as droplet dispersion during speech and cough under different environmental settings. Furthermore, the performance of the numerical framework is evaluated through strong and weak scaling analysis.
AB - Transmission of infectious respiratory diseases through airborne dispersion of viruses poses a great risk to public health. In several major diseases, one of the main modes of transmission is through respiratory droplets. Virus laden respiratory droplets and aerosols can be generated during coughing, sneezing and speaking. These droplets and aerosols can remain suspended in air and be transported by airflow posing a risk of infection in individuals who might come in contact with them. With this background, in this work, we present a numerical framework for simulation of dispersion of respiratory sputum droplets using implicit large-eddy simulations. A combination of discrete Lagrangian droplet model and fully compressible Navier-Stokes flow solver is employed in this study. The method is applied to analyze cases such as droplet dispersion during speech and cough under different environmental settings. Furthermore, the performance of the numerical framework is evaluated through strong and weak scaling analysis.
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U2 - 10.1145/3468267.3470575
DO - 10.1145/3468267.3470575
M3 - Conference contribution
AN - SCOPUS:85114332861
T3 - Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2021
BT - Proceedings of the Platform for Advanced Scientific Computing Conference, PASC 2021
PB - Association for Computing Machinery, Inc
T2 - 2021 Platform for Advanced Scientific Computing Conference, PASC 2021
Y2 - 5 July 2021 through 9 July 2021
ER -
