Marcos Batistella Lopes, Gaëlle Guyot, Nathan Mendes
Year:
2023
Languages: English | Pages: 10 pp
Bibliographic info:
43rd AIVC - 11th TightVent - 9th venticool Conference - Copenhagen, Denmark - 4-5 October 2023

The accurate estimation of the local wind pressure coefficient is crucial in the numerical modeling of natural or mixed ventilation in buildings subjected to wind. Building ventilation modeling typically relies on average wind pressure coefficient values specific to the building façade and wind direction. While the literature provides some correlations and standards for building wall-average pressure coefficients, these values are only useful in the absence of additional information or a database, as they can vary significantly based on urban forms. Field measurements, wind tunnel tests, and numerical modeling are the available methods for estimating pressure on building facades. In the first part of this study, the wall-average pressure coefficient was validated using Computational Fluid Dynamics (CFD) for both an isolated low-rise building and a non-isolated low-rise building. Acceptable relative errors were achieved for the non-isolated building in all wind directions. However, higher relative errors were observed for the non-isolated building at surface directions of 90° and 180° for wind directions exceeding 75°. In the second part of this study, a Building Energy Simulation Test was conducted to assess the impact of the pressure coefficient on ventilation modeling, comparing five scenarios: no wind action, standard pressure coefficient, literature correlation pressure coefficient, and CFD-derived pressure coefficient for isolated and non-isolated buildings. The results indicated relative differences on the order of 7% and 6% for Air Change Rate and CO2 average concentrations, respectively. This research contributes to the understanding of performance indicators for Indoor Air Quality (IAQ) studies, emphasizing the importance of considering both intentional and involuntary airflows in ventilation design.