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• W3204156787 abstract "The design of indoor airflow environments can significantly reduce the risk of respiratory epidemic infections indoors. Some studies have successfully developed theoretical models for calculating the effect of airflow fields on infection rates. However, up until now, studies have primarily focused on simulating and calculating the distribution of viral infection rates in current building scenarios. Due to the lack of a direct influence model for the design parameters and infection rate calculation, the present studies lack a quantitative analysis of the design parameters. This paper investigates the building openings design approach in a medium-sized kindergarten in Germany, intending to explore passive-based design solutions to improve the building's ability to prevent the virus' spread. We calculate the infection rate distribution in space by CFD combined with the Wells-Riley model. And then, use the Grasshopper platform to build an optimization model with the design parameters of building openings and infection rate values to discuss the relationship between geometric parameters and infection rate variation. The results show that the building openings' design parameters in transition spaces significantly affect the indoor infection rate under the condition that the input wind speed at the building openings is stable. We can see that optimizing building openings significantly reduces the average infection rate in space. The infection rate in the area with the largest decrease can be reduced by 18.41%. The distribution of infection rate in space is much more uniform, and the excess area is significantly reduced. This study has implications for future research and practice in designing public buildings under the influence of long-standing and cyclical outbreaks of epidemics." @default.
• W3204156787 created "2021-10-11" @default.
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• W3204156787 date "2021-09-25" @default.
• W3204156787 modified "2023-10-05" @default.
• W3204156787 title "Optimal design of building openings to reduce the risk of indoor respiratory epidemic infections" @default.
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• W3204156787 doi "https://doi.org/10.1007/s12273-021-0842-3" @default.
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