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<p>High-speed aircraft rudder structures face prominent flutter problems under complex operating conditions, requiring higher aeroelastic stability. This paper proposes an efficient aeroelastic optimization method based on surrogate models and optimization algorithms. A full-process analysis and optimization platform integrating sensitivity analysis, surrogate model training and optimization algorithms is built using Python. Compared with the traditional mass adjustment method that has low efficiency, the proposed optimization design process is more efficient and achieves high-precision target flutter boundaries. First, sensitivity analysis of flutter boundaries was conducted to improve optimization efficiency. Second, a rapid surrogate model for mass distribution-flutter boundaries is constructed to reduce finite element calculations and further improve analysis efficiency. Finally, particle swarm optimization is adopted with structural mass minimization as the objective function and flutter boundary improvement percentage as the constraint. For the 2 Mach rudder structure case, the method accurately predicts structural flutter boundaries. Results show 10.0 % flutter boundary improvement achieved with only 0.17 % structural mass increase, and computational efficiency improved nearly 5 times. This demonstrates significant engineering application value.</p>

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Efficient aeroelastic optimization of rudder structure based on kriging model

  • 期刊论文

  • 发表日期：

    2026年3月10日

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  • Longchao Dong,
  • Xiaochen Hang,
  • Rui Zhu,
  • Qiang Chen,
  • Dahai Zhang,
  • Qingguo Fei

摘要

High-speed aircraft rudder structures face prominent flutter problems under complex operating conditions, requiring higher aeroelastic stability. This paper proposes an efficient aeroelastic optimization method based on surrogate models and optimization algorithms. A full-process analysis and optimization platform integrating sensitivity analysis, surrogate model training and optimization algorithms is built using Python. Compared with the traditional mass adjustment method that has low efficiency, the proposed optimization design process is more efficient and achieves high-precision target flutter boundaries. First, sensitivity analysis of flutter boundaries was conducted to improve optimization efficiency. Second, a rapid surrogate model for mass distribution-flutter boundaries is constructed to reduce finite element calculations and further improve analysis efficiency. Finally, particle swarm optimization is adopted with structural mass minimization as the objective function and flutter boundary improvement percentage as the constraint. For the 2 Mach rudder structure case, the method accurately predicts structural flutter boundaries. Results show 10.0 % flutter boundary improvement achieved with only 0.17 % structural mass increase, and computational efficiency improved nearly 5 times. This demonstrates significant engineering application value.