Spatiotemporal analysis of surface pressure and wind characteristics for cross-ventilation airflow rate assessment

Yun Zhang

doi:10.17918/00001018

The ventilation with outside air has received tremendous attention since the outbreak of the COVID 19 pandemic. Wind-driven cross ventilation has been reported to be an efficient strategy to enhance the indoor and outdoor air exchange for this purpose. However, there is a lack of an accurate tool for the rapid estimation of airflow rate. The candidate pressure-based orifice equation involves two parameters, pressure coefficient, and free stream wind speed, which have not been fully understood due to its oversimplification. This work aims to fill the gap. First, a pressure-based instantaneous airflow rate (Qins) is proposed to mitigate the discrepancy between measured airflow of a series of wind tunnel tests estimated from averaged pressure. Second, a spatiotemporal analysis is carried out on instantaneous pressure to understand the turbulent flow and hence provide evidence for such fluctuation-induced airflow. At last, the spatial and temporal variation of urban wind is investigated by comparing local wind with airport wind. This work approaches these questions by investigating the underlying flow behavior. A series of wind tunnel tests were reviewed to establish the relationship between pressure and wind-driven cross-ventilation. Then, the discrepancy between airflow rate measurement and averaged pressure is justified by both a steady-state CFD simulation and a temporal analysis on instantaneous pressure. It's found when the wind is parallel to openings, a strong temporal correlation between pressure on two lateral walls results in zero time-averaged pressure difference. In contrast, the measured airflow rate is greater than zero and is more consistent with an accumulative instantaneous airflow rate (Qins) which is accounts for pressure difference over small time step. The proposed, novel K-mean clustering method detects a coherent and organized flow structure that is likely linked to von Karman vortex shedding. Such flow structures are periodic and result in intermittent pressure differences at a relatively small time step for both isolated buildings or more complex urban-like settings. It attributes to the fluctuation-induced airflow rate, which the Qins is promising to capture. The investigation on wind variation found an overall strong to moderate correlation between local wind speed and that of the airport in the three cities discussed. However, the correlation is a function of topographic features of the region, say a region with homogenous roughness (building heights) primarily indicates a strong correlation between the local and airport wind. The correlation becomes weaker when wind speed is low in the summer months. On the other hand, our studies have demonstrated systematic patterns of wind direction shifts. Future work is encouraged to better model the local wind data from airport wind under real urban environments. The potential solution to solving insufficient training data is discussed. As an attempt to understand the mechanism of fluctuation-induced cross-ventilation, the study presents systematic and generic knowledge of instantaneous flow structures induced by wind-building interaction as an alternative to other time-consuming and source-intensive methods like CFD, wind tunnel test, and field measurements. The results could be used as a semi-quantitative description of the transient behavior of flow around buildings and hence provides evidence for a periodic function that acts as the driving force for cross ventilation. Those results are beneficial in terms of natural ventilation design as well. For instance, we found that the density, surrounding building height, and building roof significantly impact the flow rate achieved by a sheltered building. A favorable building orientation could be [theta]=45 to the prevailing wind if the target building has the same height as surrounding buildings or [theta]=20 for a "moderately dense" case.

Spatiotemporal analysis of surface pressure and wind characteristics for cross-ventilation airflow rate assessment

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Spatiotemporal analysis of surface pressure and wind characteristics for cross-ventilation airflow rate assessment

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