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Bionic flight is one of the hotspots in the field of aviation research. The aerodynamic performance of Flapping wing Micro Air Vehicles (FMAV) can be significantly improved by optimization of geometry and kinematics of the flapping wing with modern optimization algorithms. In this paper, an un-steady aerodynamic optimization platform for flapping wings is built based on the surrogate optimization method, which takes into account both accuracy and efficiency. The optimization platform uses an in-house unsteady Reynolds-Averaged Navier-Stokes equation (URANS) solver for aerodynamic modeling, and the surrogate model is constructed by the optimization toolbox “SurroOpt”, which can simultaneously optimize kinematic parameters and geometry parameters of the flapping wing. A typical two-section flapping wing with a 7.4% improvement in period-averaged lift is obtained by optimizing the inner profile of wing, while ensuring that the mean thrust of the flapping wing is not less than that of the baseline wing and the mean power consumption is not greater than that of the baseline wing. This shows that the aerodynamic optimization platform built for flapping wing in this paper is effective.

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Aerodynamic Shape Optimization of Dynamic Unsteady Flapping Wings Using Surrogate-Based Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Tao Wu,
  • Qiang Jia,
  • Wei Li,
  • Dong Chen Wang,
  • Dong Xue

摘要

Bionic flight is one of the hotspots in the field of aviation research. The aerodynamic performance of Flapping wing Micro Air Vehicles (FMAV) can be significantly improved by optimization of geometry and kinematics of the flapping wing with modern optimization algorithms. In this paper, an un-steady aerodynamic optimization platform for flapping wings is built based on the surrogate optimization method, which takes into account both accuracy and efficiency. The optimization platform uses an in-house unsteady Reynolds-Averaged Navier-Stokes equation (URANS) solver for aerodynamic modeling, and the surrogate model is constructed by the optimization toolbox “SurroOpt”, which can simultaneously optimize kinematic parameters and geometry parameters of the flapping wing. A typical two-section flapping wing with a 7.4% improvement in period-averaged lift is obtained by optimizing the inner profile of wing, while ensuring that the mean thrust of the flapping wing is not less than that of the baseline wing and the mean power consumption is not greater than that of the baseline wing. This shows that the aerodynamic optimization platform built for flapping wing in this paper is effective.