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Dr EVGENIA KORSUKOVA's Outputs (4)

High-fidelity CFD-trained machine learning to inform RANS-modelled interfacial turbulence (2023)
Journal Article
Bertolotti, L., Jefferson-Loveday, R., Ambrose, S., & Korsukova, E. (2023). High-fidelity CFD-trained machine learning to inform RANS-modelled interfacial turbulence. Journal of the Global Power and Propulsion Society, 7, 269-281. https://doi.org/10.33737/jgpps/166558

In aero-engine bearing chambers, two-phase shearing flows are difficult to predict as Computational Fluid Dynamics (CFD) RANS models tend to overestimate interfacial turbulence levels, leading to inaccuracies in the modelling of the flow. Turbulence... Read More about High-fidelity CFD-trained machine learning to inform RANS-modelled interfacial turbulence.

High Fidelity Cfd-Trained Machine Learning To Inform Rans-Modelled Interfacial Turbulence (2022)
Presentation / Conference Contribution
Bertolotti, L., Jefferson-Loveday, R., Ambrose, S., & Korsukova, E. (2022, September). High Fidelity Cfd-Trained Machine Learning To Inform Rans-Modelled Interfacial Turbulence. Presented at GPPS Chania22, Chania, Greece

In aero-engine bearing chambers, two-phase shearing flows are difficult to predict as Computational Fluid Dynamics (CFD) RANS models tend to overestimate interfacial turbulence levels, leading to inaccuracies in the modelling of the flow. Turbulence... Read More about High Fidelity Cfd-Trained Machine Learning To Inform Rans-Modelled Interfacial Turbulence.

Oil scoop simulation and analysis using CFD and SPH (2016)
Presentation / Conference Contribution
Korsukova, E., Kruisbrink, A., Morvan, H., Paleo Cageao, P., & Simmons, K. (2016, June). Oil scoop simulation and analysis using CFD and SPH. Presented at ASME Turbo Expo 2016: Turbine Technical Conference and Exposition, Seoul, South Korea