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CFD simulation of airborne pathogen transport due to human activities
Computational Fluid Dynamics (CFD) is an increasingly popular tool for studying the impact of design interventions on the transport of infectious microorganisms. While much of the focus is on respiratory infections, there is substantial evidence that certain pathogens, such as those which colonise t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126191/ https://www.ncbi.nlm.nih.gov/pubmed/32288014 http://dx.doi.org/10.1016/j.buildenv.2011.06.001 |
Sumario: | Computational Fluid Dynamics (CFD) is an increasingly popular tool for studying the impact of design interventions on the transport of infectious microorganisms. While much of the focus is on respiratory infections, there is substantial evidence that certain pathogens, such as those which colonise the skin, can be released into, and transported through the air through routine activities. In these situations the bacteria is released over a volume of space, with different intensities and locations varying in time rather than being released at a single point. This paper considers the application of CFD modelling to the evaluation of risk from this type of bioaerosol generation. An experimental validation study provides a direct comparison between CFD simulations and bioaerosol distribution, showing that passive scalar and particle tracking approaches are both appropriate for small particle bioaerosols. The study introduces a zonal source, which aims to represent the time averaged release of bacteria from an activity within a zone around the entire location the release takes place. This approach is shown to perform well when validated numerically though comparison with the time averaged dispersion patterns from a transient source. However, the ability of a point source to represent such dispersion is dependent on airflow regime. The applicability of the model is demonstrated using a simulation of an isolation room representing the release of bacteria from bedmaking. |
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