A high-precision CFD method to predict dynamic derivatives

Dynamic derivatives are key aerodynamic parameters that significantly influence the flight stability and maneuverability of flying vehicles, making them crucial in design of flight control systems. With advances in CFD technology, dynamic derivatives are commonly determined through numerical simulation methods. However, traditional low-order schemes often fail to ensure the necessary prediction accuracy, highlighting the need for improvement in this area. This paper develops a high-precision numerical method for predicting dynamic derivatives for flying vehicles. The method simulates forced oscillatory unsteady flow by using a RANS equation solver enclosed by the S-A turbulence model, discretized by the fifth-order WENO-K scheme on a structured chimera grid. Dynamic derivatives are then identified through the integral method. To verify the reliability of the developed method, the pitching damping derivative for the U.S. Army-Navy Basic Finner missile is calculated across subsonic, transonic, and supersonic regimes and compared with free-flight test data. The computational results show good agreement with the test data. For a typical state of Ma=0.9, Re=6.3×10⁵, the relative errors in the pitching damping derivative, compared to a second-order scheme from two references, are reduced from 10.3% and 5.1% to 0.49%, demonstrating the method's significant improvement in prediction accuracy. This method holds substantial value for flight quality analysis and the design of flight control systems for aircrafts.