...Tianyou Chen; Le Cai; Jun Zeng; Weitao Zhang; Songtao Wang 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 based on a small...

... of loss prediction, the paper proposes a data-driven tip flow loss prediction framework for a BLI fan. It employs a neural network to build a surrogate model to predict the tip flow loss at complex non-uniform aerodynamic conditions. Physical understandings of the flow features in the BLI fan...