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My bibliography Save this articleUncertainty analysis of impact of geometric variations on turbine blade performance
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DOI: 10.1016/j.energy.2019.03.140
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- Li, Jinxing & Liu, Tianyuan & Wang, Yuqi & Xie, Yonghui, 2022. "Integrated graph deep learning framework for flow field reconstruction and performance prediction of turbomachinery," Energy, Elsevier, vol. 254(PC).
- Mahdi Erfanian Nakhchi & Shine Win Naung & Mohammad Rahmati, 2023. "Direct Numerical Simulations of Turbulent Flow over Low-Pressure Turbine Blades with Aeroelastic Vibrations and Inflow Wakes," Energies, MDPI, vol. 16(6), pages 1-21, March.
- Li, Jinxing & Liu, Tianyuan & Zhu, Guangya & Li, Yunzhu & Xie, Yonghui, 2023. "Uncertainty quantification and aerodynamic robust optimization of turbomachinery based on graph learning methods," Energy, Elsevier, vol. 273(C).
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Keywords
Turbine blade; Geometric variations; Aerodynamic performance; Uncertainty quantification; Surrogate model;All these keywords.
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