Mach Number Prediction of Wind Tunnel Flow Field Based on RBFNN and LSTM

With the development of aerodynamics, wind tunnel experiment has become an important part of aircraft development in aerospace, automobile manufacturing, bridge construction and other fields. In the process of wind tunnel experiment, the speed and accuracy of Mach number prediction directly affect the quality of wind tunnel, which needs to be accurately predicted and controlled. In this paper, a RBFNN model is adopted as the structure of Mach number prediction model for steady wind tunnel flow field, and a LSTM-based Mach number time series prediction model is established for dynamic data.