Accelerating the Adoption of LES for Next-Generation Wind Engineering
Catherine Gorlé
Biography
Catherine Gorlé is an Associate 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, 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).
Abstract
Computational fluid dynamics can support more sustainable and resilient design of buildings and cities by providing predictions of pedestrian wind comfort, air quality, thermal comfort, energy efficiency, and wind loads. Large-eddy simulation (LES) offers particular promise because it can reduce model uncertainty to levels acceptable for informing critical design decisions. This talk will explore where LES for computational wind engineering stands today, and what opportunities can be leveraged to accelerate the broader adoption of LES in engineering practice.
The first part of the talk will present a validation study demonstrating the capability of the two-step simulation approach proposed in the forthcoming ASCE pre-standard for computational wind engineering to predict peak wind pressure loads on buildings in complex urban environments. The discussion will conclude with key research directions to further advance the use of LES for wind loading predictions.
The second part of the talk will explore opportunities in education, high-performance computing, and AI to broaden the impact of LES in wind engineering design. The discussion will focus on two persistent challenges: (1) the level of expertise required to obtain reliable simulation results, and (2) the computational cost of LES analyses, particularly when accounting for the inherent variability of atmospheric flows at engineering-relevant scales. Together, developments that address these challenges may help accelerate the transition of LES from a specialized research tool to a practical technology for routine wind engineering applications.
Address
1151 Richmond Street, London, ON, N6A 3K7
cwe2026@uwo.ca
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