AERODYNAMIC DESIGN OPTIMIZATION OF CENTRIFUGAL COMPRESSOR BLADE USING PARAMETERIZED FREE-FORM DEFORMATION

被引:0
作者
Xu, Dongqiang [1 ]
Yu, Jianyang [1 ]
Shen, Jinsong [1 ]
Li, Ning [1 ]
Song, Yanping [1 ]
Yang, Xinlong [1 ]
机构
[1] Harbin Inst Technol, Sch Energy Sci & Engn, Harbin, Peoples R China
来源
PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 12D | 2024年
基金
黑龙江省自然科学基金; 中国国家自然科学基金;
关键词
Centrifugal compressor; Free-form deformation; Mesh deformation; Convolutional neural network; Optimization design;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
To address the challenges encountered during a multi-operating-point optimization of centrifugal compressor blades, including a large design space, redundant search, limited flexibility, and low optimization efficiency, this paper presents an aerodynamic optimization approach for centrifugal compressor impeller blades based on parameterized free-form deformation (FFD) and deep learning. To realize the parametric control of a compressor blade, a three-dimensional FFD control body is arranged around a blade according to the geometric characteristics. The inverse distance weighting (IDW) mesh deformation algorithm is used to extrapolate the deformation of surface mesh points to volume mesh points. Using this method, the analysis mesh can be directly updated with high quality instead of regenerating the geometry model when design variables are changed during optimization. Based on this and convolutional neural networks, a design optimization framework is established by combining the optimal Latin hypercube sample method and the NSGA-II multi-objective genetic algorithm. An optimization of the centrifugal compressor blade of a micro gas turbine was carried out, and the results showed that the total pressure ratio and isentropic efficiency at the design point was increased by 4.03% and 1.21 percentage points, respectively. The optimization results demonstrate that the developed optimization framework can effectively improve the performance of centrifugal compressors and provide support for compressor design.
引用
收藏
页数:12
相关论文
共 24 条
[11]  
Li J., 2015, STUDY COUPLING OPTIM, P56659
[12]   Aerodynamic shape optimization of a single turbine stage based on parameterized Free-Form Deformation with mapping design parameters [J].
Li, Lei ;
Jiao, Jiangkun ;
Sun, Shouyi ;
Zhao, Zhenan ;
Kang, Jialei .
ENERGY, 2019, 169 :444-455
[13]   2-EQUATION EDDY-VISCOSITY TURBULENCE MODELS FOR ENGINEERING APPLICATIONS [J].
MENTER, FR .
AIAA JOURNAL, 1994, 32 (08) :1598-1605
[14]  
Menzel S, 2005, 6 WORLD C STRUCT MUL
[15]   Metamodel-Driven Data Mining Model to Support Three-Dimensional Design of Centrifugal Compressor Stage [J].
Qin, Ruihong ;
Ju, Yaping ;
Spence, Stephen ;
Zhang, Chuhua .
JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 2021, 143 (12)
[16]   Surrogate-based aerodynamic shape optimization for delaying airfoil dynamic stall using Kriging regression and infill criteria [J].
Raul, Vishal ;
Leifsson, Leifur .
AEROSPACE SCIENCE AND TECHNOLOGY, 2021, 111
[17]   On the prediction of the reverse flow and rotating stall characteristics of high-speed axial compressors using a three-dimensional through-flow code [J].
Righi, Mauro ;
Pachidis, Vassilios ;
Konozsy, Laszlo .
AEROSPACE SCIENCE AND TECHNOLOGY, 2020, 99
[18]  
Rumelhart D.E., 1985, Readings in Cognitive Science
[19]  
Sederberg T. W., 1986, Computer Graphics, V20, P151, DOI 10.1145/15886.15903
[20]  
Shepard D., 1968, 23rd ACM National Conference, P517, DOI DOI 10.1145/800186.810616