Reduced order unsteady aerodynamic modeling for stability and control analysis using computational fluid dynamics

Abstract

Recent advances and challenges in the generation of reduced order aerodynamic models using computational fluid dynamics are presented. The models reviewed are those that can be used for aircraft stability and control analysis and include linear and nonlinear indicial response methods, Volterra theory, radial basis functions, and a surrogate-based recurrence framework. The challenges associated with identification of unknowns for each of the reduced order methods are addressed. A range of test cases, from airfoils to full aircraft, have been used to evaluate and validate the reduced order methods. The motions have different amplitudes and reduced frequencies and could start from different flight conditions including those in the transonic speed range. Overall, these reduced order models help to produce accurate predictions for a wide range of motions, but with the advantage that model predictions require orders of magnitude less time to evaluate once the model is created.