Evolutionary methods for optimal shape design

An optimisation code called Optima has been developed at the International Centre for Numerical Methods in Engineering (CIMNE). This report validates two reputably robust Evolutionary Algorithms available in Optima and employs them on aerodynamic shape optimization problems. The two schemes, Differential Evolution Scheme 1 (DE1) and Evolution Strategy coupled with Covariance Matrix adaption (ES-CMA), were tested and verified on three standard parametric optimization objective functions through comparison against existing results. Analysis of the test data allowed trends to be established and from this, settings to enhance the performance of the algorithms were proposed and substantiated.
The algorithms and their suggested settings were applied on an inverse and a direct constrained shape optimization problems involving NACA four digit aerofoils. The inverse task involves the recovery of an aerofoil profile through its pressure distribution and the direct problem entails the minimization of an objective function containing a combination of lift and drag coefficients. Simulation of the aerofoil in turbulent flow was done using a Computational Fluid Dynamics (CFD) setup.
Finally, the results are presented and the ES-CEMAmethod, using the settings CMA-B proposed in the paper, was found to be most robust. Suggestions for improvements and further work in the optimization configuration and the problem simulation are also proposed.