基于多自由度参数化降维方法的涡轮叶片高效气动优化

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关键词：主成分分析；直接操纵自由变形方法；参数化降维；涡轮叶片气动优化中图分类号：V231.3DOI：10.3969/j.issn.1004-132X.2026.02.001 开放科学（资源服务）标识码（OSID）：

Efficient Aerodynamic Optimization Method for Turbine Blades Based on Multi-degree-of-freedom Parameterized Dimensionality Reduction

HUANG Pengfei1 CHEN Jiang1 CHENG Jinxin²LI Bin1XIANG Hangl 1.School of Energy and Power Engineering，Beihang University，Beijing，100191 2.School of Mechanical Engineering，Beijing University of Technology，Beijing，100083

Abstract： In view of the high design dimension and diffculty in constructing surrogate models in the aerodynamic optimization of three-dimensional turbine blades，a multi-degree-of-freedom parameterized dimensionality reduction method was proposed to construct an eficient optimization framework，that integrated DFFD and PCA，and combined the pre-screened surrogate model assisted differential evolution （Pre-SADE） algorithm. Taking a smallgas turbine as the object，a snapshot set was generated through experimental design，and the 36-dimensional DFFD design space was mapped to the 10-dimensional basis modal coeffcient space.A concise and effective surogate model was established in the dimensionality reduction space and rapid optimization was completed. The results show that the proposed method significantly reduces the shock wave intensity and aerodynamic loss while improving the design point flow （204号 （+0.46%） and isentropic efficiency （+3.191%） ，and the optimization time is reduced by 24.58% . The study verifies the intuitiveness， effectiveness and optimization eficiency improvement advantages of this dimensionality reduction method in high-dimensional design problems，providing a more eficient and lowcost solution for blade aerodynamic optimization.

Key Words： principal component analysis（PCA）; direct manipulation free-form deformation （DFFD method；parameterized dimensionality reduction； turbine blade aerodynamic optimization

0 引言

燃气轮机是国家高端装备制造能力的重要体现，其核心部件一涡轮的气动性能直接影响整机输出功率和效率的提升[1]。（剩余14354字）