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

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Title: Integrated Surrogate Model-Based Approach for Aerodynamic Design Optimization of Three-Stage Axial Compressor in Gas Turbine Applications.
Authors: Cheng, Jinxin1,2 (AUTHOR), Li, Bin2,3 (AUTHOR), Song, Xiancheng3,4 (AUTHOR), Ji, Xinfang4,5 (AUTHOR), Zhang, Yong5,6 (AUTHOR), Chen, Jiang3,6 (AUTHOR), Xiang, Hang1,3 (AUTHOR) xhyyyh@buaa.edu.cn
Source: Energies (19961073). Sep2025, Vol. 18 Issue 17, p4514. 22p.
Subjects: Axial flow compressors, Gas turbines, Reduced-order models, Dimensional reduction algorithms, Aerodynamics, Mathematical optimization, Evolutionary algorithms, Statistical accuracy
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. [ABSTRACT FROM AUTHOR]
Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
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  Data: Integrated Surrogate Model-Based Approach for Aerodynamic Design Optimization of Three-Stage Axial Compressor in Gas Turbine Applications.
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  Data: <searchLink fieldCode="DE" term="%22Axial+flow+compressors%22">Axial flow compressors</searchLink><br /><searchLink fieldCode="DE" term="%22Gas+turbines%22">Gas turbines</searchLink><br /><searchLink fieldCode="DE" term="%22Reduced-order+models%22">Reduced-order models</searchLink><br /><searchLink fieldCode="DE" term="%22Dimensional+reduction+algorithms%22">Dimensional reduction algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Aerodynamics%22">Aerodynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Evolutionary+algorithms%22">Evolutionary algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+accuracy%22">Statistical accuracy</searchLink>
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  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/en18174514
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        Text: English
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        StartPage: 4514
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      – SubjectFull: Axial flow compressors
        Type: general
      – SubjectFull: Gas turbines
        Type: general
      – SubjectFull: Reduced-order models
        Type: general
      – SubjectFull: Dimensional reduction algorithms
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      – SubjectFull: Aerodynamics
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      – SubjectFull: Mathematical optimization
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      – SubjectFull: Evolutionary algorithms
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      – SubjectFull: Statistical accuracy
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      – TitleFull: Integrated Surrogate Model-Based Approach for Aerodynamic Design Optimization of Three-Stage Axial Compressor in Gas Turbine Applications.
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            NameFull: Cheng, Jinxin
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            – D: 01
              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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