Using large eddy simulation to study particle motions in a room.
As people spend most of their time in an indoor environment, it is important to predict indoor pollutant level in order to assess health risks. As particles are an important pollutant indoors, it is of great interest to study the airflow pattern and particle dispersion in buildings. This study uses large eddy simulation (LES) to predict three-dimensional and transient turbulent flows and a Lagrangian model to compute particle trajectories in a room. The motion of three different types of solid particles in a decaying homogeneous isotropic turbulent airflow is calculated. By comparing the computed results with the experimental data from the literature, the computational method used in this investigation is found to be successful in predicting the airflow and particle trajectories in terms of the second-order statistics, such as the mean-square displacement and turbulent intensity. This Lagrangian model is then applied to the study of particles' dispersion in a ventilated cavity with a simplified geometry for two ventilation scenarios. It is shown that light particles follow the airflow in the room and many particles are exhausted, while heavier particles deposit to the floor or/and are exhausted.


CONCLUSIONS
The results of this paper can be used to study dispersion of infectious diseases in enclosed spaces in which virus or bacteria are often attached to particles and transported to different rooms in a building through ventilation systems. In most of studies, the virus or bacteria have been considered to be gaseous phase so there is no slip between virus/bacteria and air. The results in this paper show that heavier particles are submitted to gravity and are sensitive to the ventilation strategy.
Béghein
C
C
LEPTAB, Université de La Rochelle, Avenue Michel Crépeau, La Rochelle, France.
Jiang
Y
Y
Chen
Q Y
QY
D000392:Air Movements; D016902:Air Pollution, Indoor / Q000032:analysis*; D008962:Models, Theoretical; D010316:Particle Size; D018570:Risk Assessment