Aerodynamic Optimisation using a Robust Evolutionary Algorithm and Grid-free Flowsolver

It is well known that Evolutionary Algorithms (EAs) can provide solutions to problems that are difficult to solve with conventional deterministic optimisers. In this paper, we present continuing research on the application of a modern Evolutionary Algorithm (EA) for aerodynamic shape optimisation coupled with a grid-free or meshless flowsolver based on Kinetic schemes. The evolutionary method is based upon traditional evolution strategy with the incorporation of an asynchronous function evaluation for the solution and uses a hierarchical topology where the search for the best individual takes place successively in separate hierarchical layers comprising different fidelity models/resolutions or number of points. The grid-free formulation requires the domain discretisation to have very little topological information. A simple random distribution of points along with local connectivity information is sufficient. The connectivity which contains a set of neighbouring points is used to evaluate the special derivatives appearing in the conservation law. The derivatives are evaluated using Least Square (LS) approximation. The application of the methodology is then illustrated on two-dimensional inverse aerofoil optimisation problems. Results indicate that the method is robust and efficient on its application to real world problems.