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Technical Briefs

A Study on Multidisciplinary Optimization of an Axial Compressor Blade Based on Evolutionary Algorithms

[+] Author and Article Information
Chang Luo, Liming Song, Jun Li

 Institute of Turbomachinery,  Xi’an Jiaotong University, Xi’an 710049, People’s Republic of China

Zhenping Feng1

 Institute of Turbomachinery,  Xi’an Jiaotong University, Xi’an 710049, People’s Republic of Chinazpfeng@mail.xjtu.edu.cn

1

Corresponding author.

J. Turbomach 134(5), 054501 (Apr 27, 2012) (5 pages) doi:10.1115/1.4003817 History: Received July 23, 2010; Revised January 10, 2011; Published April 27, 2012; Online April 27, 2012

An aerodynamic single disciplinary optimization and an aerodynamic/structural multidisciplinary optimization of an axial compressor blade are performed using evolutionary algorithms in this paper. The blade is optimized for maximizing its isentropic efficiency in the aerodynamic single disciplinary optimization. The isentropic efficiency of the optimum blade obtained from the aerodynamic single disciplinary optimization is 1.65% higher than that of the reference blade, however, the mechanical performance analysis indicates that it has a higher stress distribution and does not satisfy the vibration frequency constraint. In the multidisciplinary optimization, the maximum of the isentropic efficiency and the minimization of the maximum stress are selected as the design objectives. The analysis results indicate that the method of dealing with minimization of the maximum stress as a design objective is proper and that the presented multiobjective and multidisciplinary optimization method is more suitable for the optimization design of a real turbomachinery blade than the traditional heuristic aerodynamic-structural iteration.

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Copyright © 2012 by American Society of Mechanical Engineers
Topics: Optimization , Blades
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References

Figures

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Figure 1

Grids used for independent analysis

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Figure 2

Results of the calculated vibration frequencies

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Figure 3

Flow chart of the aerodynamic single disciplinary optimization method

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Figure 4

Profiles of the reference and aerodynamic optimum designs

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Figure 5

Efficiency performance curve

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Figure 6

Total pressure performance curve

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Figure 7

Flow chart of the multidisciplinary optimization method

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Figure 8

Pareto solutions of the multiobjective and multidisciplinary optimization

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Figure 9

Comparison of the geometry of the reference design and optimized designs

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