Huang, Luofeng;
Hetharia, Wolter;
Grech La Rosa, Andrea;
Tavakoli, Sasan;
Khojasteh, Danial;
Li, Minghao;
Riyadi, Soegeng;
... Thomas, Giles; + view all
(2023)
Offshore COVID-19 risk assessment based on a fishing vessel.
Ocean Engineering
, 285
(2)
, Article 115408. 10.1016/j.oceaneng.2023.115408.
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Abstract
Offshore crews often work near each other due to limited space, signifying a complex environment for the airborne transmission of the coronavirus (COVID-19). During offshore operations, a fishing vessel can be subjected to miscellaneous airflow conditions and will respond dynamically to ocean waves. To understand the risk of COVID-19 contagion, this research establishes a new computational model to analyse the airborne transmission of COVID-19 and develops effective mitigation strategies where possible. The concentration and coverage of coronavirus are scrutinised, considering typical airflows and wave-induced vessel motions. Furthermore, the COVID-19 infection risk is quantified using a probability index. The results show that the overall infection risk of a ship in tailwind is lower than in head or beam wind. Structural motions are for the first time coupled with the virus transmission, and it was found that the vessel’s oscillating movement in waves can reinforce the virus concentration in close proximity to the infected person and may help diffuse the virus outside the proximal region. The presented findings can inform the airborne contagion risks and corresponding hygienic measures for maritime and offshore operations, facilitating long-term human health in seas.
| Type: | Article |
|---|---|
| Title: | Offshore COVID-19 risk assessment based on a fishing vessel |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.oceaneng.2023.115408 |
| Publisher version: | https://doi.org/10.1016/j.oceaneng.2023.115408 |
| Language: | English |
| Additional information: | Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Computational Fluid Dynamics, Fishing Vessel, Offshore Operation, Pandemic, Particle Modelling, Particulate flow, Risk Assessment, Virus |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10174088 |
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