Development of a Prediction Model of the Pedestrian Mean Velocity Based on LES of Random Building Arrays

Abstract

Wind speed in urban areas is influenced by the interaction between wind flow and building geometry; at the pedestrian level, the interaction is more complex, particularly with high building density. This study investigated the wind velocity distribution and the mean velocity ratio at the pedestrian level using the large-eddy simulation (LES) database based on random building arrays of several plan area densities, λp. The heights of random buildings are between 0.36 h and 3.76 h where h = 0.025 m. Mean streamwise velocity profiles were obtained at the pedestrian level for all arrays and were found to decrease as λp increased. Wind flow patterns at the pedestrian level were highly influenced by adjacent buildings, especially in denser conditions, λp > 0.17. The pedestrian-level mean velocity was obtained around each building, and the relationship between the local mean velocity ratio, Vp(t) and the local frontal area density, λf(t) was analyzed. Subsequently, a prediction model was formulated based on the building’s aspect ratio, αp; the correlation for high-rise buildings with 2.64 h ≤ αp ≤ 3.76 h was high at 0.8, while a lower correlation was obtained for lower buildings due to random positioning and surrounding geometric effects. Therefore, the impact of high-rise buildings on pedestrian wind velocity can be estimated more accurately using the formulated model.