Aerodynamic and aeroacoustic optimization of rotorcraft airfoils via a parallel genetic algorithm

A parallel genetic algorithm (GA) methodology was developed to generate a f amily of two-dimensional airfoil designs that address rotorcraft aerodynami c and aeroacoustic concerns. The GA operated on 20 design variables, which constituted the control points for a spline representing the airfoil surfac e. The GA took advantage of available computer resources by operating in ei ther serial mode, where the GA and function evaluations were run on the sam e processor or "manager/worker" parallel mode, where the GA runs on the man ager processor and function evaluations are conducted independently on sepa rate worker processors. The multiple objectives of this work were to minimi ze the drag and overall noise of the airfoil. Constraints were placed on li ft coefficient, moment coefficient, and boundary-layer convergence. The aer odynamic analysis code XFOIL provided pressure and shear distributions in a ddition to lift and drag predictions. The aeroacoustic analysis code, WOPWO P, provided thickness and loading noise predictions. The airfoils comprisin g the resulting Pareto-optimal set exhibited favorable performance when com pared with typical rotorcraft airfoils under identical design conditions us ing the same analysis routines. The relationship between the quality of res ults and the analyses used in the optimization is also discussed. The new a irfoil shapes could provide starting points for further investigation.