Predicting the wind pressure coefficient distribution
on a high-rise building using computational fluid dynamics

June 24, 2020 | 11am - 12pm PST

Abstract

The prediction of pressure coefficients on high-rise buildings commonly relies on wind tunnel pressure tap measurements. However, the pressure tap resolution used in standard wind tunnel tests can be insufficient for the dimensioning of cladding components, which requires accurate calculation of the design pressure coefficient on a panel. Computational fluid dynamics offers an attractive alternative, given the potential to provide the complete three-dimensional pressure field with a spatial resolution equal to the grid resolution.

Nevertheless, it is not straightforward to guarantee that sufficiently accurate results are obtained at a reasonable computational cost. In this webinar I will present large-eddy simulation (LES) results for the pressure coefficient distribution on a high-rise building. The importance of different model choices, including the numerical schemes, grid resolution, subgrid model, and boundary conditions, will be discussed. The sensitivity of the results to the incoming surface layer characteristics will be emphasized. The LES results will be compared to high-resolution pressure tap measurements obtained at the Politecnico di Milano and the NHERI Wall of Wind experimental facilities, demonstrating that LES can be used to support cladding design.

Presenter

Catherine Gorlé is an Assistant Professor of Civil and Environmental Engineering at Stanford University. Her research activities focus on the development of predictive computational fluid dynamics (CFD) simulations to support the design of sustainable buildings and cities. Specific topics of interest are: the coupling of large- and small-scale models and experiments to quantify uncertainties related to the variability of boundary conditions, the development of uncertainty quantification methods for low-fidelity models using high-fidelity data, and the use of data assimilation to improve CFD predictions.

Catherine received her BSc (2002) and MSc (2005) degrees in Aerospace Engineering from the Delft University of Technology, and her PhD (2010) from the von Karman Institute for Fluid Dynamics in cooperation with the University of Antwerp. She has been the recipient of a Stanford Center for Turbulence Research Postdoctoral Fellowship (2010), a Pegasus Marie Curie Fellowship (2012), and an NSF CAREER award (2018).

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