Tandem Cascade Flow Prediction by POD-RBFN Reduced Order Model - SHANG Xun; LIU Hanru; DU Yican; HU Zhijie (Hangkong gongcheng jinzhan, 2022)
The cost of obtaining a large amount of flow field information by traditional experiment or CFD is unacceptable,so it is of significance to develop faster forecasting calculation methods.Proper orthogonal decomposition(POD)is used to extract the dominant mode of the tandem flow field.Radial basis function network(RBFN)is used to respond to the coefficients of the POD basis functions to realize the construction of the reduced-order prediction model of the flow field.Then the adaptive sampling method is developed for the reduced order model.The prediction model is verified by the unsteady flow field data of a cascade.It is concluded that the hybrid method can be utilized to accurately predict the aerodynamics parameters and flow field of tandem cascade.Compared with static sampling,the number of samples required for adaptive sampling to achieve the same reconstruction accuracy is reduced by about 25%.