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Research Papers

Three-Dimensional Aerodynamic Optimization for Axial-Flow Compressors Based on the Inverse Design and the Aerodynamic Parameters

[+] Author and Article Information
Liu He

School of Jet Propulsion, Beijing University of Aeronautics and Astronautics, Beijing 100191, P. R. Chinaheliu282@163.com

Peng Shan

School of Jet Propulsion, Beijing University of Aeronautics and Astronautics, Beijing 100191, P. R. Chinapshan@buaa.edu.cn

J. Turbomach 134(3), 031004 (Jul 14, 2011) (13 pages) doi:10.1115/1.4003252 History: Received May 10, 2010; Revised November 01, 2010; Published July 14, 2011; Online July 14, 2011

Integrating a genetic algorithm code with a response surface methodology code based on the artificial neural network model, this paper develops an optimization system. By introducing a quasi-three-dimensional through-flow design code and a design code of axial compressor airfoils with camber lines of arbitrary shape, and involving a three-dimensional computational fluid dynamics solver, this paper establishes a numerical aerodynamic optimization platform for the three-dimensional blades of axial compressors. The optimization in this paper mainly has four features. First, it applies the conventional inverse design method instead of the common computer aided geometric design parametrization method to generate a three-dimensional blade. Second, it chooses aerodynamic parameters with physical meaning as design variables instead of purely geometrical parameters. Third, it presents a stage-by-stage optimization strategy about the multistage turbomachinery optimization. Fourth, it introduces the visual analysis method into optimization, which can adjust variation ranges of variables by analyzing how great the variables influence the objective function. The above techniques were applied to the redesign of a single rotor row and two double-stage axial fans. The departure angles and work distributions in the inverse design were taken as design variables separately in optimizations of the single rotor and double-stage fans, and they were parametrically represented by means of Bézier curves, whose parameters were used as the optimization variables in the practical operation. The three investigated examples elucidate that not only the techniques mentioned above are appropriate and effective in engineering, but also the design guidance for similar inverse design problems can be obtained from the optimization results.

Copyright © 2012 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

The flowchart of the optimization platform

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Figure 2

The cur discrete points in the through-flow design

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Figure 3

The data sites of each chosen cur curve of all blades

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Figure 4

The control parameters of the Bézier curve of cur

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Figure 5

The CFD grids of the two-stage fan

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Figure 6

Comparison of the adiabatic efficiency lines of the different mesh numbers of the two-stage fan at the 100% speed

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Figure 7

The variation trends of the average of the target sum of the objective function versus variables in the first stage optimization of Case 1 of the two-stage fan

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Figure 8

The distribution curve, the Bézier curve, and the Bézier control points of the dimensionless departure angles on the rotor hub camber line

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Figure 9

The optimization process for the maximization of the adiabatic efficiency of the rotor

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Figure 10

Comparison of the rotor departure angle distributions

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Figure 11

Comparison of the rotor hub, middle, and tip element airfoils

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Figure 12

Comparison of the Cp distributions at the 90% and 10% rotor spans at the peak efficiency point

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Figure 13

Comparison of the meridional contours of the two double-stage axial fans in Cases 1 and 2

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Figure 14

The first stage optimization process for the maximization of the mass flow rate of the two-stage fan

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Figure 15

The root mean square error of the first stage optimization for the maximization of the mass flow rate

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Figure 16

Comparison of the dimensionless cur distribution curves of all the four blade rows in the through-flow design

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Figure 17

Comparison of the hub, middle, and tip element airfoils of the two-stage fan blades

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Figure 18

The fan 100% speed performances

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Figure 19

Comparison of the relative flow angles at the inlet and the dimensionless ρcz at the outlet along the span of the fan

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Figure 20

Comparison of the relative Mach number contours at the 50% span at the design point

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Figure 21

Comparison of the Cp distributions of two rotors at the 90%, 50%, and 10% spans at the design point

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Figure 22

Comparison of the streamlines near the suction surfaces at the design point

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Figure 23

The SEQV distributions of the two rotors after optimization

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Figure 24

The first stage optimization process for the maximization of the adiabatic efficiency of the two-stage fan

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Figure 25

Comparison of the dimensionless cur distribution curves of all the four blade rows in the through-flow design

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Figure 26

Comparison of the hub, middle, and tip element airfoils of the two-stage fan blades

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Figure 27

The fan 100% speed performances

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Figure 28

Comparison of the relative Mach number contours at the 50% span at the design point

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Figure 29

Comparison of the Cp distributions of Stator1 and Rotor2 at the 90%, 50%, and 10% spans at the design point

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Figure 30

Comparison of the streamlines near the suction surfaces at the design point

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Figure 31

Comparison of the Cp distributions of Stator1 at the 50% and 10% spans at the design point in Case 1

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Figure 32

Comparison of the hub, middle, and tip velocity triangles at the inlet and outlet of Rotor1 in Case 1

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