Vorspel, Lena and Schramm, Matthias and Stoevesandt, Bernhard and Brunold, Luca and Bünner, Martin
(2017)
A benchmark study on the efficiency of unconstrained optimization algorithms in 2D-aerodynamic shape design.
Cogent Engineering, 4 (1).
ISSN 2331-1916
Abstract
Optimization algorithms are used in various engineering applications to identify optimal shapes. In this work, we benchmark several unconstrained optimization algorithms (Nelder–Mead, Quasi-Newton, steepest descent) under variation of gradient estimation schemes (adjoint equations, 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: (a) computation time, and (b) applicability and ease of use. Results for lift optimizations are presented for airfoils at a Reynolds number of Re=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 a low number of design variables. For intermediate and large number of design variables, gradient-based algorithms with gradient estimation through the solution of adjoint equations are unbeaten.
Item Type: |
Article
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Additional Information: |
Publiziert mit Hilfe des DFG-geförderten Open Access-Publikationsfonds der Carl von Ossietzky Universität Oldenburg. |
Uncontrolled Keywords: |
airfoil optimization, airfoil parametrization, computational fluid dynamics, OpenFOAM, gradient-based, gradient-free, adjoint approach, optimization, automatic design |
Subjects: |
Generalities, computers, information > Computer science, internet |
Divisions: |
Faculty of Mathematics and Science > Institute of Physics (IfP) |
Date Deposited: |
28 Sep 2017 13:26 |
Last Modified: |
20 Oct 2017 11:07 |
URI: |
https://oops.uni-oldenburg.de/id/eprint/3354 |
URN: |
urn:nbn:de:gbv:715-oops-34353 |
DOI: |
doi:10.1080/23311916.2017.1354509 |
Nutzungslizenz: |
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