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RISAerodynamic Performance Prediction for Wide-Incidence Turbines Using Graph Neural Network Models Driven by Small-Scale Experimental Data
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: To rapidly and accurately predict turbine rotor blade losses within a wide range of incidences (−50–30 deg), graph neural networks (GNNs) are utilized to predict the aerodynamic parameters of two-dimensional turbine blades ...
Enhancing Aerodynamic Performance of a Non-Axisymmetric Endwall Contoured Cascade Through Section Profiling Method
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Endwall contouring and 3D blade configurations are effective techniques for enhancing turbomachinery performance. The integration of these technologies is an important area of investigation. To continue the numerical and ...
Endwall Contouring for Improving Aerodynamic Performance in a High-Pressure Turbine Cascade
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The endwall contouring has proven to be an effective technique in controlling the impacts of secondary flow within turbomachinery. A baseline cascade with the original axisymmetric endwall (BASE) has been redesigned with ...