RT info:eu-repo/semantics/article
T1 Influence of human breathing modes on airborne cross infection risk
A1 Villafruela Espina, José Manuel
A1 Olmedo Cortés, Inés
A1 San José Alonso, Julio Francisco
K1 airborne cross infection risk
K1 human exhalation flow
K1 CFD
K1 transient
K1 displacement ventilation
K1 human microenvironment
AB CFD simulation is an accurate and reliable method to predict the risk of airborne cross-infection in a room. This paper focuses on the validation of a 3-D transient CFD model used to predict personal exposure to airborne pathogens and infection risk in a displacement ventilated room. The model provides spatial and temporal solutions of the airflow pattern in the room (temperature, velocity and turbulence), as well as contaminant concentration in a room where two thermal manikins simulate two standing people, one of whom exhales a tracer gas N2O simulating airborne contaminants. Numerical results are validated with experimental data and the model shows a high accuracy when predicting the transient cases studied. Once the model is validated, the CFD model is used to simulate different airborne cross-infection risk scenarios. Four different combinations of the manikins’ breathing modes and four different separation distances between the two manikins are studied. The results show that exhaling through the nose or mouth disperses exhaled contaminants in a completely different way and also means that exhaled contaminants are received differently. For short separation distances between breathing sources the interaction between breaths is a key factor in the airborne cross-infection for all the breathing mode combinations studied. However, for long distances the general airflow conditions in the room prove to be more important.
PB Elsevier
SN 03601323
YR 2016
FD 2016
LK http://uvadoc.uva.es/handle/10324/33056
UL http://uvadoc.uva.es/handle/10324/33056
LA eng
NO Building and Environment Volume 106, 1 September 2016, Pages 340-351
NO Producción Científica
DS UVaDOC
RD 22-dic-2024