Catherine Gorlé 
- (2024): Comparison of measured and LES-predicted wind pressures on the Space Needle. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 249 (June 2024).
- (2024): Design and demonstration of a sensing network for full-scale wind pressure measurements on buildings. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 250 (July 2024).
- (2023): Investigation of peak wind loading on a high-rise building in the atmospheric boundary layer using large-eddy simulations. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 236 (May 2023).
- (2023): Characterizing spatial variability in the temperature field to support thermal model validation in a naturally ventilated building. In: Journal of Building Performance Simulation, v. 16, n. 4 (January 2023).
- (2022): Large-Eddy Simulations of Wind-Driven Cross Ventilation, Part 2: Comparison of Ventilation Performance Under Different Ventilation Configurations. In: Frontiers in Built Environment, v. 8 (February 2022).
- (2022): Large-Eddy Simulations of Wind-Driven Cross Ventilation, Part1: Validation and Sensitivity Study. In: Frontiers in Built Environment, v. 8 (February 2022).
- (2022): Full-scale validation of CFD simulations of buoyancy-driven ventilation in a three-story office building. In: Building and Environment, v. 221 (August 2022).
- (2022): Improving the predictive capability of building simulations using uncertainty quantification. In: Science and Technology for the Built Environment, v. 28, n. 5 (April 2022).
- (2022): Improving thermal model predictions for naturally ventilated buildings using large eddy simulations. In: Building and Environment, v. 220 (July 2022).
- (2022): Wind tunnel pressure data analysis for peak cladding load estimation on a high-rise building. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 220 (January 2022).
- (2022): Optimal temperature sensor placement in buildings with buoyancy-driven natural ventilation using computational fluid dynamics and uncertainty quantification. In: Building and Environment, v. 207 (January 2022).
- (2021): A multi-fidelity machine learning framework to predict wind loads on buildings. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 214 (July 2021).
- (2018): Uncertainty quantification for modeling night-time ventilation in Stanford’s Y2E2 building. In: Energy and Buildings, v. 168 (June 2018).
- (2020): Sensitivity of LES predictions of wind loading on a high-rise building to the inflow boundary condition. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 206 (November 2020).
- (2020): Comparison of high resolution pressure measurements on a high-rise building in a closed and open-section wind tunnel. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 204 (September 2020).
- (2019): Computational urban flow predictions with Bayesian inference: Validation with field data. In: Building and Environment, v. 154 (May 2019).
- (2018): Improving urban flow predictions through data assimilation. In: Building and Environment, v. 132 (March 2018).
- (2018): Optimizing turbulent inflow conditions for large-eddy simulations of the atmospheric boundary layer. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 177 (June 2018).
- (2015): Quantifying inflow and RANS turbulence model form uncertainties for wind engineering flows. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 144 (September 2015).
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