The predictions of infection risk of indoor airborne transmission of diseases in high-rise hospitals

Tracer gas simulation

Taesub Lim, Jinkyun Cho, Byungseon Kim

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

The spread of diseases from infected patients within hospitals is resulting in many human casualties. If a virus were to be transmitted through uncontrolled air movement within a hospital and were then to infect other patients or healthy visitors, it would be impossible to contain the spread of the disease. The purpose of this paper is to apply reliable boundary conditions based on previous studies in order to analyze the airflow pattern caused by the stack effect in high-rise hospitals. An analysis was carried out on the vertical airborne transmission of viruses according to the location of the infected patients. The horizontal airborne transmission based on the characteristics of the supply air diffuser and return air grille was also analyzed by using the multi-zone airflow simulation and tracer gas (CFD) simulation. In addition, this paper explored solutions to prevent the spread of airborne pathogenic bacteria by analyzing various alternatives of HVAC systems and basic data on ventilation system planning for high-rise hospitals.

Original languageEnglish
Pages (from-to)1172-1181
Number of pages10
JournalEnergy and Buildings
Volume42
Issue number8
DOIs
Publication statusPublished - 2010 Aug 1

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Gases
Viruses
Air
Diffusers (fluid)
Ventilation
Bacteria
Computational fluid dynamics
Boundary conditions
Planning
HVAC

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Building and Construction

Cite this

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The predictions of infection risk of indoor airborne transmission of diseases in high-rise hospitals : Tracer gas simulation. / Lim, Taesub; Cho, Jinkyun; Kim, Byungseon.

In: Energy and Buildings, Vol. 42, No. 8, 01.08.2010, p. 1172-1181.

Research output: Contribution to journalArticle

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