Shape Optimization of Multi-Element Airfoils Using Evolutionary Algorithms and Hybrid Unstructured Framework

In this paper we present design optimization studies of multi-element airfoils utilizing evolutionary algorithms. The shape optimization process is carried out by utilization of high fidelity CFD based comprehensive framework. The framework comprises of a genetic algorithm based design optimization procedure coupled to the hybrid unstructured CRUNCH CFD^® code and a grid generator. The genetic algorithm based optimization procedure is very robust, and searches the complex design landscape in an efficient and parallel manner. Furthermore, it can easily handle complexities in constraints and objectives and is disinclined to get trapped in local extrema regions. The fitness evaluations are carried out through a RANS based hybrid unstructured solver. The utilization of hybrid unstructured methodology provides flexibility in incorporating large changes in design and mesh regeneration is carried out in an automated manner through a scripting process within the grid generator GRIDGEN. The design optimization procedure is carried out simultaneously on both the stabilizer and the flap. Shape changes to the trailing edge of the flap strongly influence the secondary flow patterns that set up in the gap region between the stabilizer and the flap. These, in turn, are found to have a profound influence on lift and torque characteristics. The paper will discuss these results and provide details of the optimization procedure including coupling with hybrid unstructured framework and grid generator.