Computational Fluid Dynamics Analysis on the Effect of Bioaerosol Dispersion on Regional Railway Configuration in the United Kingdom During Busy Hours

Musa Alhassan, Rakesh Mishra, Naeem Mian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Since the outbreak of the novel corona virus (COVID-19) disease in 2019 that spread throughout the world, studies relating to the internal environments have become increasingly important. Computational fluid dynamics has been used to investigate the effect of aerosol droplet dispersion on the air distribution configuration in the regional railway coach in the United Kingdom which employs the supply air inlet ports on the ceiling and the exhaust air outlets are located above each of the windows. Investigation on two different scenarios of occupants in the railway coach has been conducted and analyzed. The first scenario has 30 passengers which is assumed to be the less busy hours of the day, 29 passengers are assumed to be seated and 1 passenger who is set as the infected individual is assumed to be walking towards his seat. Similarly, the second scenario has 100 passengers (full capacity) which is assumed to be the busiest hour of the day with 99 of the passengers seated already and 1 passenger walking towards his seat. Passengers standing with no seat have been ignored. Cough and sneeze droplet dispersion are analyzed to understand their effect on the passengers inside the railway coach and the distance that the droplet particles can travel inside the railway coach. This paper presents a CFD analysis of bioaerosol dispersion in regional railway coaches during busy hours in the UK, revealing that coaches with 36 supply air inlets display superior droplet transmission and uniform airflow, resulting in improved air quality and no significant difference when the railway coach is at full capacity or lower capacity.
Original languageEnglish
Title of host publicationProceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023)
EditorsAndrew D. Ball, Huajiang Ouyang, Jyoti K. Sinha, Zuolu Wang
PublisherSpringer, Cham
Number of pages11
ISBN (Electronic)9783031494130
ISBN (Print)9783031494123, 9783031494154
Publication statusPublished - 30 May 2024
EventThe UNIfied Conference of DAMAS, InCoME and TEPEN Conferences - Huddersfield, United Kingdom, Huddersfield, United Kingdom
Duration: 29 Aug 20231 Sep 2023

Publication series

NameMechanisms and Machine Science
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992


ConferenceThe UNIfied Conference of DAMAS, InCoME and TEPEN Conferences
Abbreviated titleUNIfied 2023
Country/TerritoryUnited Kingdom
Internet address

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