Catherine Gorlé

1.9k total citations
62 papers, 1.5k citations indexed

About

Catherine Gorlé is a scholar working on Environmental Engineering, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Catherine Gorlé has authored 62 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Environmental Engineering, 27 papers in Computational Mechanics and 26 papers in Aerospace Engineering. Recurrent topics in Catherine Gorlé's work include Wind and Air Flow Studies (41 papers), Fluid Dynamics and Turbulent Flows (16 papers) and Aerodynamics and Fluid Dynamics Research (14 papers). Catherine Gorlé is often cited by papers focused on Wind and Air Flow Studies (41 papers), Fluid Dynamics and Turbulent Flows (16 papers) and Aerodynamics and Fluid Dynamics Research (14 papers). Catherine Gorlé collaborates with scholars based in United States, Belgium and Italy. Catherine Gorlé's co-authors include Jeroen van Beeck, Clara García‐Sánchez, Gianluca Iaccarino, Alessandro Parente, C. Benocci, G. Van Tendeloo, Patrick Rambaud, Jorge Sousa, David Philips and Kenneth E. Goodson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Atmospheric Environment and Energy and Buildings.

In The Last Decade

Catherine Gorlé

57 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Catherine Gorlé United States 22 960 510 504 301 184 62 1.5k
A.U. Weerasuriya Hong Kong 23 1.1k 1.2× 562 1.1× 271 0.5× 177 0.6× 44 0.2× 53 1.4k
Antti Hellsten Finland 19 1.2k 1.2× 680 1.3× 623 1.2× 282 0.9× 106 0.6× 50 1.7k
J. A. Peterka United States 22 1.1k 1.1× 631 1.2× 807 1.6× 273 0.9× 147 0.8× 75 1.7k
Peter Irwin United States 23 1.2k 1.2× 490 1.0× 633 1.3× 293 1.0× 111 0.6× 85 1.6k
K.T. Tse Hong Kong 22 832 0.9× 399 0.8× 466 0.9× 123 0.4× 183 1.0× 50 1.3k
Hachimi Fellouah Canada 18 427 0.4× 550 1.1× 599 1.2× 66 0.2× 249 1.4× 68 1.2k
Patrick Rambaud Belgium 15 280 0.3× 454 0.9× 424 0.8× 77 0.3× 142 0.8× 83 909
Cruz Y. Li China 19 516 0.5× 292 0.6× 454 0.9× 39 0.1× 49 0.3× 55 900
Zheng-Tong Xie United Kingdom 21 1.6k 1.7× 818 1.6× 979 1.9× 498 1.7× 61 0.3× 62 2.0k
Kevin B. McGrattan United States 26 546 0.6× 697 1.4× 464 0.9× 74 0.2× 27 0.1× 99 2.2k

Countries citing papers authored by Catherine Gorlé

Since Specialization
Citations

This map shows the geographic impact of Catherine Gorlé's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Catherine Gorlé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Catherine Gorlé more than expected).

Fields of papers citing papers by Catherine Gorlé

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Catherine Gorlé. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Catherine Gorlé. The network helps show where Catherine Gorlé may publish in the future.

Co-authorship network of co-authors of Catherine Gorlé

This figure shows the co-authorship network connecting the top 25 collaborators of Catherine Gorlé. A scholar is included among the top collaborators of Catherine Gorlé based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Catherine Gorlé. Catherine Gorlé is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gorlé, Catherine, et al.. (2025). From large-eddy simulations to deep learning: A U-net model for fast urban canopy flow predictions. Sustainable Cities and Society. 135. 107005–107005. 1 indexed citations
2.
3.
Gorlé, Catherine, et al.. (2025). A (co-)kriging multi-fidelity framework for wind loading predictions. Journal of Building Engineering. 110. 112940–112940. 2 indexed citations
4.
Gorlé, Catherine, et al.. (2024). Design and demonstration of a sensing network for full-scale wind pressure measurements on buildings. Journal of Wind Engineering and Industrial Aerodynamics. 250. 105760–105760. 6 indexed citations
5.
Gorlé, Catherine, et al.. (2024). Comparison of measured and LES-predicted wind pressures on the Space Needle. Journal of Wind Engineering and Industrial Aerodynamics. 249. 105749–105749. 8 indexed citations
6.
Gorlé, Catherine, et al.. (2024). A predictive large-eddy simulation framework for the analysis of wind loads on a realistic low-rise building geometry. Journal of Wind Engineering and Industrial Aerodynamics. 256. 105950–105950. 5 indexed citations
7.
Bay, Christopher J., et al.. (2024). FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization. Wind Energy. 27(12). 1563–1580. 2 indexed citations
8.
9.
Philips, David, et al.. (2023). Investigation of peak wind loading on a high-rise building in the atmospheric boundary layer using large-eddy simulations. Journal of Wind Engineering and Industrial Aerodynamics. 236. 105408–105408. 22 indexed citations
10.
Gorlé, Catherine, et al.. (2023). Large-eddy simulations to define building-specific similarity relationships for natural ventilation flow rates. SHILAP Revista de lepidopterología. 3. 6 indexed citations
11.
Gorlé, Catherine, et al.. (2023). Data-driven wake model parameter estimation to analyze effects of wake superposition. Journal of Renewable and Sustainable Energy. 15(6). 3 indexed citations
12.
Gorlé, Catherine, et al.. (2021). A multi-fidelity machine learning framework to predict wind loads on buildings. Journal of Wind Engineering and Industrial Aerodynamics. 214. 104647–104647. 35 indexed citations
13.
Schito, Paolo, et al.. (2021). Wind tunnel pressure data analysis for peak cladding load estimation on a high-rise building. Journal of Wind Engineering and Industrial Aerodynamics. 220. 104855–104855. 12 indexed citations
14.
Bar‐Cohen, Avram, Mehdi Asheghi, Timothy Chainer, et al.. (2021). The ICECool Fundamentals Effort on Evaporative Cooling of Microelectronics. IEEE Transactions on Components Packaging and Manufacturing Technology. 11(10). 1546–1564. 58 indexed citations
15.
Gorlé, Catherine, et al.. (2020). Sensitivity of LES predictions of wind loading on a high-rise building to the inflow boundary condition. Journal of Wind Engineering and Industrial Aerodynamics. 206. 104370–104370. 34 indexed citations
16.
Zasso, Alberto, et al.. (2020). Comparison of high resolution pressure measurements on a high-rise building in a closed and open-section wind tunnel. Journal of Wind Engineering and Industrial Aerodynamics. 204. 104247–104247. 22 indexed citations
17.
Gorlé, Catherine, Pritish R. Parida, Farzad Houshmand, Mehdi Asheghi, & Kenneth E. Goodson. (2014). Volume-Of-Fluid Simulation for Predicting Two-Phase Cooling in a Microchannel. Bulletin of the American Physical Society. 8 indexed citations
18.
Larsson, Johan, Michael Emory, Paul G. Constantine, et al.. (2012). Quantification of multiple types of uncertainties in the HyShot II scramjet. Bulletin of the American Physical Society. 1 indexed citations
19.
Parente, Alessandro, Catherine Gorlé, Jeroen van Beeck, & C. Benocci. (2011). A Comprehensive Modelling Approach for the Neutral Atmospheric Boundary Layer: Consistent Inflow Conditions, Wall Function and Turbulence Model. Boundary-Layer Meteorology. 140(3). 411–428. 79 indexed citations
20.
Rodrigo, Javier Sanz, et al.. (2007). Aerodynamic Design of the Princess Elizabeth Antarctic Research Station.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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Rankless by CCL
2026