CFD Analysis of Indoor Ventilation for Airborne Virus Infection

Kaishan Feng, Yoshiki Yanagita, Yuko Miyamura, Adi Azriff Basri, Mohammad Zuber, Siti Rohani, Kamarul Arifin Ahmad, Masaaki Tamagawa

Research output: Contribution to journalArticlepeer-review

Abstract

Indoor airflow patterns and air residence times significantly influence the spread of airborne infectious viruses, such as COVID-19. These factors can be quantified using computational fluid dynamics (CFD). In this study, CFD was utilized to assess the indoor airflow patterns and calculate air residence times in a typical restroom with high personnel flow and low ventilation efficiency. The results identified regions with high air residence times, indicating potential risk areas for airborne virus retention. Furthermore, the effects of different ventilation strategies on these high-risk areas were analyzed. Despite meeting air change standards, certain regions were found to potentially pose a higher risk due to prolonged air residence times. Based on these findings, recommendations for improving ventilation systems to reduce the risk of airborne virus infection were proposed. This study highlights the necessity of a more nuanced approach to indoor air assessment than simply calculating air changes per hour. It was concluded that (1) different ventilation strategies can greatly affect the air residence time in the room and (2) the variance of air residence time in the air circulation area are large in some locations, even with simple ventilation adjustments.

Original languageEnglish
Pages (from-to)1-16
Number of pages16
JournalJournal of Advanced Research in Numerical Heat Transfer
Volume14
Issue number1
DOIs
Publication statusPublished - 09-2023

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Aerospace Engineering
  • Automotive Engineering
  • Computational Mechanics
  • Environmental Science (miscellaneous)

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