Abstract:
Dynamic stability derivatives are a measure of how the flight forces and moments acting on a flight body change in response to flight state. Computational Fluid Dynamics (CFD) is increasingly being used to both augment and create an aerodynamic performance database for different configurations such as aircrafts, automobiles, missiles, Unmanned Air Vehicles (UAVs) and so on. CFD currently provides an accurate and efficient estimate of the static stability derivatives, as these involve a steady-state simulation about a fixed geometry. However, the complexity for the calculation of higher-order dynamic stability derivatives for general configurations increases by multiple folds. The need for more efficient, general CFD methods is especially acute as predicting dynamic derivatives with traditional methods, such as wind tunnel testing, is expensive and difficult. As aircraft designs continue to evolve towards highly-maneuverable unmanned systems, high-fidelity aerodynamic databases including dynamic derivatives are required to accurately predict performance and develop stability and control laws.
