Volume 14, Issue 5 (Journal of Control, Vol. 14, No. 5, Special Issue on COVID-19 2021)                   JoC 2021, 14(5): 15-22 | Back to browse issues page

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Mohebbi Najm Abad J, Alizadeh R, Mesgarpour M. Prediction of the spread of Corona-virus carrying droplets in a metro wagon - A computational based artificial intelligence approach. JoC. 2021; 14 (5) :15-22
URL: http://joc.kntu.ac.ir/article-1-822-en.html
1- Islamic Azad University, Quchan, Iran
2- King Mongkut's University of Technology Thonburi (KMUTT), Bangmod, Bangkok
Abstract:   (586 Views)
Assessing the risk of transmitting the coronavirus is essential for protecting public health under the COVID-19 epidemic. Public transportation such as buses and metro wagon is the most important COVID-19 dispersion source. In the last decade, numerical simulation plays a vital role in predicting. In this case study, a combination of numerical simulation and artificial intelligence tries to predict the droplet of the sneezing process. As a case study, the Metro wagon was considered, and droplet dispersion along the bus was studied. The result indicated that the small diameter could easily transport along with the wagon. It also shows that the large area under affected by particle deposition. In this case study, a combination of numerical simulation and artificial intelligence has a great result.
Full-Text [PDF 1057 kb]   (136 Downloads)    
Type of Article: Research paper | Subject: COVID-19
Received: 2020/12/30 | Accepted: 2021/02/13 | Published: 2021/02/28

References
1. Chen, L.-D., 2020, Effects of Ambient Temperature and Humidity on Droplet Lifetime-A Perspective of Exhalation Sneeze Droplets with COVID-19 Virus Transmission. International Journal of Hygiene and Environmental Health, p. 113568. [DOI:10.1016/j.ijheh.2020.113568]
2. Meccariello, G. and O. Gallo, 2020, What ENT doctors should know about COVID-19 contagion risks. Authorea Preprints.
3. Diwan, S.S., et al., 2020, Understanding Transmission Dynamics of COVID-19-Type Infections by Direct Numerical Simulations of Cough/Sneeze Flows. Transactions of the Indian National Academy of Engineering, p. 1. [DOI:10.1007/s41403-020-00106-w]
4. Rockett, R.J., et al., 2020, Revealing COVID-19 transmission in Australia by SARS-CoV-2 genome sequencing and agent-based modeling. Nature medicine. 26(9): p. 1398-1404. [DOI:10.1038/s41591-020-1000-7]
5. Enserink, M. and K. Kupferschmidt, 2020, With COVID-19, modeling takes on life and death importance. 2020, American Association for the Advancement of Science. [DOI:10.1126/science.367.6485.1414-b]
6. Ivorra, B., et al., 2020, Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China. Communications in nonlinear science and numerical simulation,. 88: p. 105303. [DOI:10.1016/j.cnsns.2020.105303]
7. Chaudhuri, S., et al., 2020, Modeling the role of respiratory droplets in Covid-19 type pandemics. Physics of Fluids, 32(6): p. 063309. [DOI:10.1063/5.0015984]
8. Abuhegazy, M., et al., 2020, Numerical investigation of aerosol transport in a classroom with relevance to COVID-19. Physics of Fluids, 32(10): p. 103311. [DOI:10.1063/5.0029118]
9. Hassani, K. and S. Khorramymehr, 2019, In silico investigation of sneezing in a full real human upper airway using computational fluid dynamics method. Computer methods and programs in biomedicine, 177: p. 203-209. [DOI:10.1016/j.cmpb.2019.05.031]
10. Singh, R.K. and S.N. Tripathi, 2020, Application of National Aerosol Facility (NAF) in Designing of a Ventilation System for Isolation Rooms to Minimize Interpersonal Exposure of Sneezing/Coughing. Transactions of the Indian National Academy of Engineering, p. 1. [DOI:10.1007/s41403-020-00102-0]
11. Kotb, H. and E.E. Khalil, 2020, Impact of Sneezed and Coughed Droplets Produced from a Moving Passenger on Other Passengers inside Aircraft Cabins. in AIAA Propulsion and Energy 2020 Forum. [DOI:10.2514/6.2020-3949]
12. Hasan, A., 2020, Tracking the Flu Virus in a Room Mechanical Ventilation Using CFD Tools and Effective Disinfection of an HVAC System. International Journal of Air-Conditioning and Refrigeration, 28(02): p. 2050019. [DOI:10.1142/S2010132520500194]
13. Busco, G., et al., 2020, Sneezing and asymptomatic virus transmission. Physics of Fluids, 32(7): p. 073309. [DOI:10.1063/5.0019090]
14. Verma, S., M. Dhanak, and J. Frankenfield, 2020, Visualizing droplet dispersal for face shields and masks with exhalation valves. Physics of Fluids, 32(9): p. 091701. [DOI:10.1063/5.0022968]
15. Li, H., et al., 2020, Dispersion of evaporating cough droplets in tropical outdoor environment. Physics of Fluids, 32(11): p. 113301. [DOI:10.1063/5.0026360]
16. Christodoulou, L., et al., 2020, State prediction of an entropy wave advecting through a turbulent channel flow. Journal of Fluid Mechanics, 882. [DOI:10.1017/jfm.2019.799]
17. Alizadeh, R., et al., 2020, Application of Machine Learning to Investigation of Heat and Mass Transfer Over a Cylinder Surrounded by Porous Media-The Radial Basic Function Network. Journal of Energy Resources Technology, p. 1-18. [DOI:10.1115/1.4047402]
18. Abad, J.M.N., et al., 2020, Analysis of transport processes in a reacting flow of hybrid nanofluid around a bluff-body embedded in porous media using artificial neural network and particle swarm optimization. Journal of Molecular Liquids, p. 113492. [DOI:10.1016/j.molliq.2020.113492]
19. Yeoh, G.H. and J. Tu, 2019, Computational techniques for multiphase flows. Butterworth-Heinemann. [DOI:10.1016/B978-0-08-102453-9.00003-9]
20. Kolev, N.I. and N.I. Kolev, 2007, Multiphase flow dynamics: Fundamentals. Vol. 1. Springer. [DOI:10.1007/3-540-69833-7_1]
21. Crowe, C.T., et al., 2011, Multiphase flows with droplets and particles. CRC press. [DOI:10.1201/b11103]
22. Pope, S.B., 2001, Turbulent flows., IOP Publishing. [DOI:10.1017/CBO9780511840531]
23. Gupta, J., C.H. Lin, and Q. Chen, 2009, Flow dynamics and characterization of a cough. Indoor air, 19(6): p. 517-525. [DOI:10.1111/j.1600-0668.2009.00619.x]
24. Busco, G., et al., 2020, Sneezing and asymptomatic virus transmission. Physics of Fluids, 32(7): p. 073309. [DOI:10.1063/5.0019090]
25. Broomhead, D and D. Lowe, 1988, Multivariable functional interpolation and adaptive networks. Complex Systems, no. 2 ,p. 321-355.

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