International Journal of Aeronautical and Space Sciences

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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A Highly Efficient Aeroelastic Optimization Method Based on a Surrogate Model

  • Zhiqiang, Wan (School of Aeronautic Science and Engineering, Beihang University) ;
  • Xiaozhe, Wang (School of Aeronautic Science and Engineering, Beihang University) ;
  • Chao, Yang (School of Aeronautic Science and Engineering, Beihang University)
  • Received : 2016.04.27
  • Accepted : 2016.11.21
  • Published : 2016.12.30
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Abstract

This paper presents a highly efficient aeroelastic optimization method based on a surrogate model; the model is verified by considering the case of a high-aspect-ratio composite wing. Optimization frameworks using the Kriging model and genetic algorithm (GA), the Kriging model and improved particle swarm optimization (IPSO), and the back propagation neural network model (BP) and IPSO are presented. The feasibility of the method is verified, as the model can improve the optimization efficiency while also satisfying the engineering requirements. Moreover, the effects of the number of design variables and number of constraints on the optimization efficiency and objective function are analysed in detail. The accuracy of two surrogate models in aeroelastic optimization is also compared. The Kriging model is constructed more conveniently, and its predictive accuracy of the aeroelastic responses also satisfies the engineering requirements. According to the case of a high-aspect-ratio composite wing, the GA is better at global optimization.

Keywords

Acknowledgement

Supported by : National Key Research and Development Program, National Natural Science Foundation of China

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