This article presents a two-step optimization based on a surrogate model for the aerodynamic shape optimization in a viscous flow. The first-step employs the genetic algorithm (GA) to search the range of the global optimal solution. The surrogate model gappy proper orthogonal decomposition (POD) is used to replace computational dluid dynamics to estimate the flow solution, and an improvement is made on the snapshots to raise the accuracy of the gappy POD. The second-step optimization employs the steepest descent algorithm (SDA) based on the Navier-Stokes equations to refine the result of the first-step optimization. The Hicks-Henne bump function, by which the airfoil shape is parameterized, is improved to overcome its inherent flaw at the trailing edge of the airfoil. Finally, the results of the inverse design for different shapes of the airfoil and the optimal design in different states of freestream flow demonstrate that the two-step optimization is efficient and practical for the airfoil design in the viscous flow.
DUAN Yanhui, CAI Jinsheng, LIU Qiuhong
. Surrogate Model Based Optimization for Airfoil Design[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2011
, 32(4)
: 617
-627
.
DOI: CNKI:11-1929/V.20101221.0954.056
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