In this paper a systematic approach to the optimization of 2D blade profiles is presented. A genetic optimizer has been developed which modifies the blade profile and calculates its profile loss. This process is automatic, producing profile designs significantly faster and with significantly lower loss than has previously been possible.
The optimizer developed uses a genetic algorithm to optimize a 2D profile, defined using 17 parameters, for minimum loss with a given flow condition. The optimizer works with a “population” of 2D profiles with varied parameters. A CFD mesh is generated for each profile, and the result is analyzed using a 2D blade to blade solver, written for steady viscous compressible flow, to determine profile loss. The loss is used as the measure of a profile’s “fitness”. The optimizer uses this information to select the members of the next population, applying crossovers, mutations, and elitism in the process. Using this method the optimizer tends towards the best values for the parameters defining the profile with minimum loss.