Assessment of the wind flow prediction in urban environments using the CpSimulator platform

BRE, FACUNDO; GIMENEZ, JUAN M.

Weimar

Conferencia; BauSIM2022; 2022

IBPSA, International Building Performance Simulation Association

Wind pressure coefficients (Cp) data are essential input parameters for natural ventilation (NV) models. CpSimulator has shown to overcome the significant limitation to NV modeling in real applications because of the lack of simple but still reliable tools to predict Cp data on buildings with arbitrary shapes and surrounding conditions. To this end, the cloud-based platform performs fully unattended computational fluid dynamics (CFD) simulations of the atmospheric boundary layer and gets reliable Cp data for actual scenarios. This work aims to evaluate the capacity and accuracy of the CpSimulator to predict wind flow in urban environments. A validation benchmark test that comprises a high-rise building surrounded by a group of low-rise buildings is chosen to be reproduced. Initially, the ability of the platform to automatically process the input geometry, reconstruct and locate it in a CFD computational domain is evaluated. Then, after an auto-meshing of the CFD domain, flow field results are got for three wind incidences. The numerical results are compared with the wind tunnel experimental data for Cp and wind speed values.