Aerodynamic and Aeroacoustic Optimization of Rotorcraft Airfoils via a Parallel Genetic Algorithm

Abstract

A parallel genetic algorithm (GA) methodology was developed to generate a family of two-dimensional airfoil designs that address rotorcraft aerodynamic and aeroacoustic concerns. The GA operated on 20 design variables, whichconstitutedthecontrolpointsforasplinerepresentingtheairfoilsurface.TheGAtookadvantageofavailable computer resources by operating in either serial mode, where the GA and function evaluations were run on the same processor or “ manager/worker” parallel mode, where the GA runs on the manager processor and function evaluations areconducted independently on separate workerprocessors. The multiple objectives of this work were to minimizethedrag and overall noiseof the airfoil. Constraintswereplaced on liftcoefe cient, moment coefe cient, andboundary-layerconvergence.TheaerodynamicanalysiscodeXFOILprovidedpressureandsheardistributions in addition to liftand drag predictions. Theaeroacousticanalysis code, WOPWOP, provided thicknessand loading noise predictions. The airfoils comprising the resulting Pareto-optimal set exhibited favorable performance when compared with typical rotorcraft airfoils under identical design conditions using the same analysis routines. The relationship between the quality of results and the analyses used in the optimization is also discussed. The new airfoil shapes could provide starting points for further investigation.