Multi Objective Aerodynamic Optimisation by Means of Robust and Efficient Genetic Algorithm
Carlo Poloni · Notes on numerical fluid mechanics · 1999
In this paper the use of Genetic Algorithms for multi objective optimisation in aerodynamic optimisation is outlined. After a review of existing GA methodologies the operators considered at present the most promising one are described. A simple mathematical test is used for preliminary algorithmic perfomance while in more applicative cases the pressure reconstruction problem of two conflicting aerodynamic profiles is used as benchmark. A full potential transonic solver is at first used showing the performances of the optimisation algorithm employed while final results are obtained using a commercial Navier-Stokes solver with k-e turbulence modelling to reconstruct the geometry of two airfoils working at Mach=0.2 Re=5E6 and Mach=0.77 Re=19.6E6. Even thogh the test case presented might not have a practical application, it shows that direct multi objective optimisation with Navier Stokes solver can be faced with GA.