Bio


Gorlé 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. Afterwards she was a Postdoctoral Fellow at the Center for Turbulence Research at Stanford University and a Research Professor at the von Karman Institute funded by a Pegasus Marie Curie fellowship. Before joining the Civil & Environmental Engineering Department at Stanford she was an Assistant Professor in the Department of Civil Engineering & Engineering Mechanics at Columbia University.

Gorle's research focuses on the development of predictive flow 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 field measurements to validate and improve computational predictions.

Academic Appointments


  • Assistant Professor, Civil and Environmental Engineering

Professional Education


  • BSc, Delft University of Technology, Aerospace Engineering (2002)
  • MSc, Delft University of Technology, Aerospace Engineering (2005)
  • PhD, Von Karman Institute for Fluid Dynamics, Environmental and Applied Fluid Dynamics (2010)

Current Research and Scholarly Interests


Gorle's research focuses on the development of predictive flow 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 field measurements to validate and improve computational predictions.

All Publications


  • Improving urban flow predictions through data assimilation BUILDING AND ENVIRONMENT Sousa, J., Garcia-Sanchez, C., Gorle, C. 2018; 132: 282–90
  • Optimizing turbulent inflow conditions for large-eddy simulations of the atmospheric boundary layer. Journal of Wind Engineering and Industrial Aerodynamics Lamberti, G., Garcia-Sanchez, C., Sousa, J., Gorle, C. 2018; 177: 32-44
  • Uncertainty Quantification for modeling night-time ventilation in Stanford's Y2E2 building. Energy and Buildings Lamberti, G., Gorlé, C. 2018; 168: 319-330
  • Uncertainty quantification for microscale CFD simulations based on input from mesoscale codes. Journal of Wind Engineering and Industrial Aerodynamics Garcia-Sanchez, C., Gorlé, C. 2018; 176: 87-97
  • RAMS sensitivity to grid spacing and grid aspect ratio in Large-Eddy Simulations of the dry neutral Atmospheric Boundary Layer COMPUTERS & FLUIDS Ercolani, G., Gorle, C., Corbari, C., Mancini, M. 2017; 146: 59-73
  • Quantifying inflow uncertainties in RANS simulations of urban pollutant dispersion Atmospheric Environment Garcia-Sanchez, C., Van Tendeloo, G., Gorle, C. 2017; 161: 263-273
  • Thermal Modeling of Extreme Heat Flux Microchannel Coolers for GaN-on-SiC Semiconductor Devices JOURNAL OF ELECTRONIC PACKAGING Lee, H., Agonafer, D. D., Won, Y., Houshmand, F., Gorle, C., Asheghi, M., Goodson, K. E. 2016; 138 (1)

    View details for DOI 10.1115/1.4032655

    View details for Web of Science ID 000372735400008

  • RAMS and WRF sensitivity to grid spacing in large-eddy simulations of the dry convective boundary layer COMPUTERS & FLUIDS Ercolani, G., Gorle, C., Garcia-Sanchez, C., Corbari, C., Mancini, M. 2015; 123: 54-71
  • Quantifying inflow and RANS turbulence model form uncertainties for wind engineering flows JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS Gorle, C., Garcia-Sanchez, C., Iaccarino, G. 2015; 144: 202-212
  • Quantifying inflow uncertainties for CFD simulations of the flow in downtown Oklahoma City BUILDING AND ENVIRONMENT Garcia-Sanchez, C., Philips, D. A., Gorle, C. 2014; 78: 118-129
  • The deviation from parallel shear flow as an indicator of linear eddy-viscosity model inaccuracy PHYSICS OF FLUIDS Gorle, C., Larsson, J., EMORY, M., Iaccarino, G. 2014; 26 (5)

    View details for DOI 10.1063/1.4876577

    View details for Web of Science ID 000337103900002

  • A framework for epistemic uncertainty quantification of turbulent scalar flux models for Reynolds-averaged Navier-Stokes simulations PHYSICS OF FLUIDS Gorle, C., Iaccarino, G. 2013; 25 (5)

    View details for DOI 10.1063/1.4807067

    View details for Web of Science ID 000320001200043

  • A Comprehensive Modelling Approach for the Neutral Atmospheric Boundary Layer: Consistent Inflow Conditions, Wall Function and Turbulence Model BOUNDARY-LAYER METEOROLOGY Parente, A., Gorle, C., van Beeck, J., Benocci, C. 2011; 140 (3): 411-428
  • Improved kappa-epsilon model and wall function formulation for the RANS simulation of ABL flows 5th International Symposium on Computational Wind Engineering (CWE2010) Parente, A., Gorle, C., van Beeck, J., Benocci, C. ELSEVIER SCIENCE BV. 2011: 267–78
  • Dispersion in the Wake of a Rectangular Building: Validation of Two Reynolds-Averaged Navier-Stokes Modelling Approaches BOUNDARY-LAYER METEOROLOGY Gorle, C., van Beeck, J., Rambaud, P. 2010; 137 (1): 115-133
  • Stack gas dispersion measurements with Large Scale-PIV, Aspiration Probes and Light Scattering Techniques and comparison with CFD ATMOSPHERIC ENVIRONMENT Nakiboglu, G., Gorle, C., Horvath, I., van Beeck, J., Blocken, B. 2009; 43 (21): 3396-3406
  • CFD modelling of small particle dispersion: The influence of the turbulence kinetic energy in the atmospheric boundary layer ATMOSPHERIC ENVIRONMENT Gorle, C., van Beeck, J., Rarnbaud, P., Van Tendeloo, G. 2009; 43 (3): 673-681
  • Flow analyses in the lower airways: Patient-specific model and boundary conditions MEDICAL ENGINEERING & PHYSICS De Backer, J. W., Vos, W. G., Gorle, C. D., Germonpre, P., Partoens, B., Wuyts, F. L., Parizel, P. M., De Backer, W. 2008; 30 (7): 872-879

    Abstract

    Computational fluid dynamics (CFD) is increasingly applied in the respiratory domain. The ability to simulate the flow through a bifurcating tubular system has increased the insight into the internal flow dynamics and the particular characteristics of respiratory flows such as secondary motions and inertial effects. The next step in the evolution is to apply the technique to patient-specific cases, in order to provide more information about pathological airways. This study presents a patient-specific approach where both the geometry and the boundary conditions (BC) are based on individual imaging methods using computed tomography (CT). The internal flow distribution of a 73-year-old female suffering from chronic obstructive pulmonary disease (COPD) is assessed. The validation is performed through the comparison of lung ventilation with gamma scintigraphy. The results show that in order to obtain agreement within the accuracy limits of the gamma scintigraphy scan, both the patient-specific geometry and the BC (driving pressure) play a crucial role. A minimal invasive test (CT scan) supplied enough information to perform an accurate CFD analysis. In the end it was possible to capture the pathological features of the respiratory system using the imaging and computational fluid dynamics techniques. This brings the introduction of this new technique in the clinical practice one step closer.

    View details for DOI 10.1016/j.medengphy.2007.11.002

    View details for Web of Science ID 000259768300009

    View details for PubMedID 18096425