Research Papers

Novel Compressor Blade Shaping Through a Free-Form Method

[+] Author and Article Information
Alistair John

Department of Mechanical Engineering,
University of Sheffield,
Sheffield S1 3JD, UK
e-mail: adjohn1@sheffield.ac.uk

Shahrokh Shahpar

Rolls-Royce plc.,
Derby DE24 8BJ, UK
e-mail: shahrokh.shahpar@rolls-royce.com

Ning Qin

Department of Mechanical Engineering,
University of Sheffield,
Sheffield S1 3JD, UK
e-mail: n.qin@sheffield.ac.uk

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received September 7, 2016; final manuscript received December 24, 2016; published online March 15, 2017. Editor: Kenneth Hall.

J. Turbomach 139(8), 081002 (Mar 15, 2017) (11 pages) Paper No: TURBO-16-1228; doi: 10.1115/1.4035833 History: Received September 07, 2016; Revised December 24, 2016

This paper describes the use of the free-form-deformation (FFD) parameterization method to create a novel blade shape for a highly loaded, transonic axial compressor. The novel geometry makes use of precompression (via an S-shaping of the blade around midspan) to weaken the shock and improve the aerodynamic performance. It is shown how free-form-deformation offers superior flexibility over traditionally used parameterization methods. The novel design (produced via an efficient optimization method) is presented and the resulting flow is analyzed in detail. The efficiency benefit is over 2%, surpassing other results in the literature for the same geometry. The precompression effect of the S-shape is analyzed and explained, and the entropy increase across the shock (along the midblade line) is shown to be reduced by almost 80%. Adjoint surface sensitivity analysis of the datum and optimized designs is presented, showing that the S-shape is located in the region predicted to be most significant for changes in efficiency. Finally, the off-design performance of the blade is analyzed across the rotor characteristics at various speeds.

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Fig. 1

Meridional view of NASA Rotor 37 [12]

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Fig. 2

Representation of NASA Rotor 37

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Fig. 3

Example of an FFD grid in 2D

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Fig. 4

Example of a 3D FFD control grids (datum orange, perturbed blue)

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Fig. 5

Fine PADRAM mesh: (a) radial slice near LE and (b) meridional view

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Fig. 6

Rotor 37 CFD domain

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Fig. 7

Simulated characteristics versus experiment

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Fig. 8

Radial profiles versus experiment

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Fig. 9

Suction surface: (a) adjoint sensitivities and (b) limiting streamlines with 3D streamlines and reverse flow volume

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Fig. 10

(a) Suction surface pressure distribution and (b) slice of entropy just downstream of shock

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Fig. 11

SOPHY optimization flowchart

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Fig. 12

Typical MAM optimization history

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Fig. 13

Midspan optimized FFD control points

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Fig. 14

Comparison of 2D blade shapes

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Fig. 15

Relative Mach number contour comparison at: 30% (a), 50% (b), and 70% (c) span

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Fig. 16

Suction surface static pressure contours: (a) datum and (b) optimum

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Fig. 17

Datum static pressure contours

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Fig. 18

Optimized geometry static pressure contours showing the precompression effect

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Fig. 19

Schematic of shock structures: (a) datum and (b) optimized

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Fig. 20

Relative Mach number and entropy along midblade line at 70% span

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Fig. 21

Coefficient of pressure at 70% span

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Fig. 22

Adjoint surface sensitivities (efficiency): (a) datum and (b) optimized

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Fig. 23

Characteristics of datum and optimized designs

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Fig. 24

Effect of skewing the optimized blade

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Fig. 25

Varying rotational speed

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Fig. 26

Radial efficiency profiles for datum and optimized blades




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