Abstract.In an urban environment where buildings are closely packed, natural ventilation performance is undesirably disturbed by the effect of surrounding buildings. Cross-ventilation refers to the regulation of air within a building, which is essential in providing good air quality and thermal comfort for the occupants. Thus, this study focuses on the impact of packing density on ventilation rate of cross-ventilated buildings. The numerical estimation is performed by means of computational fluid dynamic (CFD) using the Reynolds Averaged Navier-Stokes (RANS) with RNG k -ε (RNG) turbulence model. Three configurations of simplified generic cubes which are regularly aligned with packing density of 25%, 35%, and 50% were considered. Velocity distribution around and inside the buildings as well as the ventilation rate are analysed. The case with packing density of 25% exhibits a reduction of 90% in the ventilation rate compared to the isolated case and continues to decrease as the packing density increase up to 35%. However, further increase of packing density up to 50%, slightly increases the ventilation rate. Hence, the result of this study imposed that surrounding buildings have a substantial influence on ventilation performance of cross-ventilated buildings.
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.
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