Unsteady Airfoil Design Optimization with Application to Dynamic Stall

One of the persistent problems affecting the aerodynamic performance of rotorcrafts is retreating blade stall that results in large pitching moments and hazardous control situations. Our primary goal is the development of an unsteady design optimization framework that can be applied to refine rotorcraft blade designs by delaying the onset of stall, and improving aerodynamic performance as well as lift cycle hysteresis. The proposed unsteady optimization framework utilizes an evolutionary algorithm, automated shape parameterization tool and a novel CFD derived analysis methodology for evaluating the objective function. The novel part of the framework is the unsteady analysis procedure that combines CFD, a modified Proper Orthogonal Decomposition Procedure (POD) and an Artificial Neural Network (ANN) to evaluate the objective function with the accuracy of a time-spectral method but at a fraction of the cost. The framework is readily applicable to Multi-Disciplinary Optimization (MDO) thereby leading to the inclusion of aero-elastic and aero-acoustic effects with minimal development. In Phase I we will demonstrate the applicability of the proposed framework to the shape optimization of a pitching airfoil without stall. In Phase II the problem of shape optimization with dynamic stall on a three-dimensional rotorcraft blade with and without MDO will be attempted.