Integrated Surrogate Model-Based Approach for Aerodynamic Design Optimization of Three-Stage Axial Compressor in Gas Turbine Applications

Jinxin Cheng, Bin Li, Xiancheng Song, Xinfang Ji, Yong Zhang, Jiang Chen and Hang Xiang ()
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Jinxin Cheng: School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100081, China
Bin Li: School of Energy and Power Engineering, Beihang University, Beijing 100191, China
Xiancheng Song: Beijing Institute of Precision Mechatronics and Controls, Beijing 100076, China
Xinfang Ji: School of Computer Science and Engineering, North Minzu University, Yinchuan 750030, China
Yong Zhang: School of Computer Science, China University of Mining and Technology, Xuzhou 221008, China
Jiang Chen: School of Energy and Power Engineering, Beihang University, Beijing 100191, China
Hang Xiang: School of Energy and Power Engineering, Beihang University, Beijing 100191, China

Energies, 2025, vol. 18, issue 17, 1-22

Abstract: The refined aerodynamic design optimization of multistage compressors is a typical high-dimensional and expensive optimization problem. This study proposes an integrated surrogate model-assisted evolutionary algorithm combined with a Directly Manipulated Free-Form Deformation (DFFD)-based parametric dimensionality reduction method, establishing a high-precision and efficient global parallel aerodynamic optimization platform for multistage axial compressors. The DFFD method achieves a balance between flexibility and low-dimensional characteristics by directly controlling the surface points of blades, which demonstrates a particular suitability for the aerodynamic design optimization of multistage axial compressors. The integrated surrogate model enhances prediction accuracy by simultaneously identifying optimal solutions and the most uncertain solutions, effectively addressing highly nonlinear design space challenges. A three-stage axial compressor in a heavy-duty gas turbine is selected as the optimization object. The results demonstrate that the optimization task takes less than 48 h and achieves an improvement of 0.6% and 4% in the adiabatic efficiency and surge margin, respectively, while maintaining a nearly unchanged flow rate and pressure ratio at the design point. The proposed approach provides an efficient and reliable solution for complex aerodynamic optimization problems.

Keywords: axial compressor; aerodynamic design optimization; directly manipulated free-form deformation; prescreening surrogate model; differential evolutionary algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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