| Citation: | ZHANG Wei, WANG Qiang, LU Jiachen, et al. Robust optimization design under geometric uncertainty based on PCA-HicksHenne method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(12): 2473-2481. doi: 10.13700/j.bh.1001-5965.2021.0142(in Chinese)
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The aerodynamic shape design of an aircraft requires a robust optimization approach that takes uncertainty into account. To the knowledge of the authors, research efforts were more paid to the robust optimization considering environmental perturbations, rather than geometric perturbations. For purpose of quantifying the geometric uncertainty, the principal component analysis (PCA) method was utilized to perform research on the parameterization process of the RAE2822 airfoil. The main geometric transformation modes of the airfoil were revealed subsequently. After that, the sensitivity analysis method was applied, and the thickness deformation mode, the camber deformation mode, and the axial displacement mode of the maximum thickness position on the upper surface were indicated as the main influential modes. Those modes were taken as the perturbation modes in the following robust optimization research. The results show that the lift variation of the deterministic optimal airfoil without consideration of perturbation is much huger, with the standard deviation increased by about 200%. However, the optimal airfoil considering geometric perturbation is more robust. The robust airfoil's variability, whether in lift or drag, are lower than those of the original RAE2822 airfoil along with the improvement in mean performance.
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