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A platform for research: civil engineering, architecture and urbanism
Numerical studies on issues of Re-independence for indoor airflow and pollutant dispersion within an isolated building
This study conducted the numerical models validated by wind-tunnel experiments to investigate the issues of Re-independence of indoor airflow and pollutant dispersion within an isolated building. The window Reynolds number (Rew) was specified to characterize the indoor flow and dispersion. The indicators of RRC (ratio of relative change) or DR (K_DR) (difference ratio of dimensionless concentration) ≤ 5% were applied to quantitatively determine the critical Rew for indoor flow and turbulent diffusion. The results show that the critical Re (Recrit) value is position-dependent, and Recrit at the most unfavorable position should be suggested as the optimal value within the whole areas of interest. Thus ReH,crit = 27,000 is recommended for the outdoor flows; while Rew,crit = 15,000 is determined for the indoor flows due to the lower part below the window showing the most unfavorable. The suggested Rew,crit (=15,000) for indoor airflow and cross ventilation is independence of the window size. Moreover, taking K_DR ≤ 5% as the indicator, the suggested Rew,crit for ensuring indoor pollutant diffusion enter the Re-independence regime should also be 15,000, indicating that indoor passive diffusion is completely determined by the flow structures. The contours of dimensionless velocity (U/U0) and concentration (K) against the increasing Rew further confirmed this critical value. This study further reveals the Re-independence issues for indoor flow and dispersion to ensure the reliability of the data obtained by reduced-scale numerical or wind-tunnel models.
Numerical studies on issues of Re-independence for indoor airflow and pollutant dispersion within an isolated building
This study conducted the numerical models validated by wind-tunnel experiments to investigate the issues of Re-independence of indoor airflow and pollutant dispersion within an isolated building. The window Reynolds number (Rew) was specified to characterize the indoor flow and dispersion. The indicators of RRC (ratio of relative change) or DR (K_DR) (difference ratio of dimensionless concentration) ≤ 5% were applied to quantitatively determine the critical Rew for indoor flow and turbulent diffusion. The results show that the critical Re (Recrit) value is position-dependent, and Recrit at the most unfavorable position should be suggested as the optimal value within the whole areas of interest. Thus ReH,crit = 27,000 is recommended for the outdoor flows; while Rew,crit = 15,000 is determined for the indoor flows due to the lower part below the window showing the most unfavorable. The suggested Rew,crit (=15,000) for indoor airflow and cross ventilation is independence of the window size. Moreover, taking K_DR ≤ 5% as the indicator, the suggested Rew,crit for ensuring indoor pollutant diffusion enter the Re-independence regime should also be 15,000, indicating that indoor passive diffusion is completely determined by the flow structures. The contours of dimensionless velocity (U/U0) and concentration (K) against the increasing Rew further confirmed this critical value. This study further reveals the Re-independence issues for indoor flow and dispersion to ensure the reliability of the data obtained by reduced-scale numerical or wind-tunnel models.
Numerical studies on issues of Re-independence for indoor airflow and pollutant dispersion within an isolated building
Build. Simul.
Cui, Peng-Yi (author) / Chen, Wei-Qiu (author) / Wang, Jia-Qi (author) / Zhang, Jin-Hao (author) / Huang, Yuan-Dong (author) / Tao, Wen-Quan (author)
Building Simulation ; 15 ; 1259-1276
2022-07-01
18 pages
Article (Journal)
Electronic Resource
English
Influence of Local Airflow on the Pollutant Emission from Indoor Building Surfaces
| Wiley | 2001
Numerical studies of indoor airflow and particle dispersion by large Eddy simulation
| Online Contents | 2007
Numerical studies of indoor airflow and particle dispersion by large Eddy simulation
| British Library Online Contents | 2007