Abstract
The wind speed varies significantly within a neighborhood due to building and vegetation size and position. A good estimation of these spatial variations is useful for several applications (outdoor thermal comfort, air pollution, building energy consumption and thermal comfort, etc.) but might be time-consuming using Computational Fluid Dynamic tools and difficult to produce for non experts.URock is a Python library that has been developped within UMEP, a city-based climate service tool integrated as plug-in in the free and open source QGIS software. It is based on the Röckle approach already used in non open source softwares such as QUIC-URB and SkyHelios: first an initial wind field is set according to empirical laws derived from wind tunnel observations; second the mass air flow is balanced minimizing the modifications of the initial wind field. This method is less accurate than traditional CFD method but quicker and simple to implement for non specialists. This work presents the evaluation of URock against wind tunnel observations.
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