Review of optimization design methods for compressor blade geometry and aerodynamic performance

被引：0
|
作者：
Huang S. [1 ,2 ]
Wang P. [1 ,2 ]
Wang Y. [1 ,2 ]
机构：
[1] Second Power System Department, AVIC Jincheng Nanjing Electromechanical and Hydraulic Engineering Research Center, Nanjing
[2] Key Laboratory of Integrated Aviation Science and Technology, Aviation Electromechanical System of AVIC, Nanjing
来源：
Tuijin Jishu/Journal of Propulsion Technology | 2024年 / 45卷 / 04期
关键词：
Compressor; Machine learning; Optimization algorithm; Optimization design; Review; Uncertainty;
D O I：
10.13675/j.cnki.tjjs.2211068
中图分类号：
学科分类号：
摘要：
The optimal design can effectively reduce the dependence on manual design experience, improve the difficulty of compressor geometric aerodynamic performance design and shorten the compressor design cycle. Firstly, in order to overcome the three major problems of high-dimensional, time-consuming, and black-box in the geometric aerodynamic performance optimization design of compressor blades, the research progress in the past 40 years in three aspects of compressor aerodynamic shape parameterization method, numerical calculation technology and optimization algorithm is reviewed in this paper. Secondly, the research progress of machine learning and data mining, uncertainty-based robust optimization design theory is summarized. Finally, it is pointed out that the optimization design can explore the optimal aerodynamic performance limit of compressor geometry, and the development direction of the compressor blade aerodynamic optimal design method is summarized and prospected. © 2024 Journal of Propulsion Technology. All rights reserved.
引用
收藏
相关论文
共 152 条
  • [1] 17, 1, pp. 1-15, (2002)
  • [2] 29, 2, pp. 257-266, (2008)
  • [3] SHAN S, WANG G G., Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive black-box functions[J], Structural and Multidisciplinary Optimization, 41, 2, pp. 219-241, (2010)
  • [4] YOSHIMURA M, IZUI K., Machine system design optimization strategies based on expansion and contraction of design spaces, St. Louis：7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, (1998)
  • [5] LI Z H, ZHENG X Q., Review of design optimization methods for turbomachinery aerodynamics[J], Progress in Aerospace Sciences, 93, pp. 1-23, (2017)
  • [6] STEINERT W, EISENBERG B, STARKEN H., Design and testing of a controlled diffusion airfoil cascade for industrial axial flow compressor application[J], Journal of Turbomachinery, 113, 4, pp. 583-590, (1991)
  • [7] SONG B, NG W, SONODA T, Et al., Loss mechanisms of high-turning supercritical compressor cascades[J], Journal of Propulsion and Power, 24, 3, pp. 416-423, (2008)
  • [8] SHREEVE R P, ELAZAR Y, DREON J W, Et al., Wake measurements and loss evaluation in a controlled diffusion compressor cascade[J], Journal of Turbomachinery, 113, 4, pp. 591-599, (1991)
  • [9] KULFAN B, BUSSOLETTI J, Fundamental”parameteric geometry representations for aircraft component shapes [C], Portsmouth：11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, (2006)
  • [10] SEDERBERG T W, PARRY S R., Free-form deformation of solid geometric models[J], ACM SIGGRAPH Computer Graphics, 20, 4, pp. 151-160, (1986)
12345678910