Indoor pollutant mixing time in an isothermal closed room: an investigation using CFD

Abstract

We report computational fluid dynamics (CFD) predictions of mixing time of a point pulse release of a pollutant in an unventilated mechanically mixed isothermal room. The aims of the study are to determine (1) the adequacy of the standard RANS two-equation (k-ε) turbulence model to predict the mixing times under these conditions, and (2) the extent to which the mixing time is a feature of the room airflow, rather than the source location within the room. CFD simulations modeled the twelve mixing time experiments performed by Drescher et al. (1995) in an isothermal sealed room for a point pulse release. Predictions of mixing time were found in good agreement with experimental measurements, over an order of magnitude variation in blower power. Additional CFD simulations were performed to investigate the relation between pollutant mixing time and pollutant source location. Seventeen source locations were investigated for five different blower power configurations in the room. Results clearly show large dependence of the mixing time on the room airflow, with some dependence on source location. We further explore dependence of mixing time on the local airflow properties (velocity and turbulence intensity) at the source location. Implications for our findings for positioning air-toxic sensors in rooms are also discussed.

Distribution of respiratory droplets in enclosed environments under different air distribution methods

“…During point pulse release of pollutants (i.e., sneezing or coughing) well-mixing conditions may not be achieved before the pollutants are ventilated outside the room. By validating their simulation against experiments, Gadgil et al (2003) found that the mixing process depends primarily on the mean airflow in the room and secondarily on the pollutant source location. This finding is in agreement with our results shown in Fig.…”

Indoor aerosol modeling for assessment of exposure and respiratory tract deposited dose

“…Hussein and Kulmala, 2008;Thatcher et al, 2002). Otherwise, spatial variation of indoor aerosol particle concentrations must be taken into account by, for example, utilizing Computational Fluid Dynamic (CFD) models (Hussein et al, 2005b;Gadgil et al, 2003;Feustel, 1999). In practice, the mass-balance equation is easier to adopt in exposure analysis.…”

Particle Deposition and Decay in a Chamber and the Implications to Exposure Assessment

“…The reason not to choose a larger volume is that both the deposition rate loss coefficient and the ITF are only meaningful under well-mixed condition and it may not hold for a very large volume and (Furtaw et al, 1996;Gadgil et al, 2003) and supermicron particles (Chen et al, 2005). Two air exchange rates 0.2 and 2 hr −1 are chosen to represent low and high values encountered in natural ventilation for buildings (Wallace et al, 2002).…”