MATEC Web Conf.
Volume 111, 2017Fluids and Chemical Engineering Conference (FluidsChE 2017)
|Number of page(s)||5|
|Section||Advances in Fluids Flow and Mechanics|
|Published online||20 June 2017|
Numerical estimation of natural ventilation of cubical urban arrays with different packing density
1 Department of Mechanical Precision Engineering, Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia
2 Engineering Department, UTM Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, Kuala Lumpur, 54100 Kuala Lumpur, Malaysia
* Corresponding author: firstname.lastname@example.org
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.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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