Vorspel, L.L.VorspelSchramm, M.M.SchrammStoevesandt, B.B.StoevesandtBrunold, L.L.BrunoldBünner, M.M.Bünner2022-03-052022-03-052017https://publica.fraunhofer.de/handle/publica/24909110.1080/23311916.2017.13545092-s2.0-85027152449Optimization algorithms are used in various engineering applications to identify optimal shapes. We benchmark several unconstrained optimization algorithms (Nelder-Mead, Quasi-Newton, steepest descent) under variation of gradient estimation schemes (adjoint approach, finite differences). Flow fields are computed by solving the Reynolds-Averaged Navier-Stokes equations using the open source computational fluid dynamics code OpenFOAM. Design variables vary from N = 2 to N = 364. The efficiency of the optimization algorithms are benchmarked in terms of computation time, applicability and ease of use. Results for lift optimizations are presented for airfoils at a Reynolds number of 50,000. As a result, we find for a small number of design variables N_5 or less, the computational efficiency of all optimization algorithms to be similar, while the ease of use of the Nelder-Mead algorithm makes it a perfect choice. For intermediate and large number of design variables, gradient-based algorithms with gradient estimation through the solution of adjoint equations are unbeaten.enjournal article