GT2020-14445 High-Fidelity Simulations of a High-Pressure Turbine Vane Subject to Large Disturbances: Effect of Exit Mach Number on Losses

von Zhao, Yaomin
Veröffentlicht in ASME Turbo Expo (2020 : Online) Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition - 2020 ; Volume 2, B (2020)

GT2021-58816 High-Fidelity Simulations of a High-Pressure Turbine Vane With End Walls: Impact of Secondary Structures and Spanwise Temperature Profiles on Losses

von Zhao, Yaomin
Veröffentlicht in ASME Turbo Expo (2021 : Online) Proceedings of ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition ; Volume 2, B: Turbomachinery: Axial flow turbine aerodynamics; deposition, erosion, fouling, and icing (2021)

GT2021-58995 High-Fidelity Simulations of a High-Pressure Turbine Stage: Effects of Reynolds Number and Inlet Turbulence

von Zhao, Yaomin
Veröffentlicht in ASME Turbo Expo (2021 : Online) Proceedings of ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition ; Volume 2, B: Turbomachinery: Axial flow turbine aerodynamics; deposition, erosion, fouling, and icing (2021)

GT2022-82370 High-Fidelity Simulation Study of the Unsteady Flow Effects on High-Pressure Turbine Blade Performance

von Leggett, John
Veröffentlicht in ASME Turbo Expo (67. : 2022 : Rotterdam) Proceedings of ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition (GT 2022) ; Volume 10, D: Turbomachinery: Multidisciplinary design approaches, optimization, and uncertainty quantification; turbomachinery general interest; unsteady flows in turbomachinery (2022)

GT2020-14732 Integration of Machine Learning and Computational Fluid Dynamics to Develop Turbulence Models for Improved Turbine Wake Mixing Prediction

von Akolekar, Harshal D.
Veröffentlicht in ASME Turbo Expo (2020 : Online) Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition - 2020 ; Volume 2, C (2020)

GT2021-59436 Turbomachinery Loss Analysis: The Relationship Between Mechanical Work Potential and Entropy Analyses

von Leggett, John
Veröffentlicht in ASME Turbo Expo (2021 : Online) Proceedings of ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition ; Volume 2, C: Turbomachinery: Design methods and CFD modeling for turbomachinery; ducts, noise, and component interactions (2021)

GT2022-81091 Multi-Objective Development of Machine-Learnt Closures for Fully Integrated Transition and Wake Mixing Predictions in Low Pressure Turbines

von Akolekar, Harshal D.
Veröffentlicht in ASME Turbo Expo (67. : 2022 : Rotterdam) Proceedings of ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition (GT 2022) ; Volume 10, C: Turbomachinery: Design methods and CFD modeling for turbomachinery; ducts, noise, and component interactions (2022)

A Data-Driven Approach for Generalizing the Laminar Kinetic Energy Model for Separation and Bypass Transition in Low- and High-Pressure Turbines

von Fang, Yuan
Veröffentlicht in ASME Turbo Expo (2023 : Boston, Mass.) Proceedings of ASME Turbo Expo 2023: Turbomachinery Technical Conference and Exposition (GT 2023) ; Volume 13, C: Turbomachinery: Deposition, erosion, fouling, and icing; design methods and CFD modeling for turbomachinery; ducts, noise, and component interactions (2023)