Research Papers

Transonic Compressor Blade Optimization Integrated With Circumferential Groove Casing Treatment

[+] Author and Article Information
Weimin Song, Yufei Zhang, Kaiwen Deng

School of Aerospace Engineering,
Tsinghua University,
Beijing 100084, China

Haixin Chen

School of Aerospace Engineering,
Tsinghua University,
Beijing 100084, China
e-mail: chenhaixin@tsinghua.edu.cn

1Corresponding author.

Manuscript received April 28, 2018; final manuscript received October 6, 2018; published online February 8, 2019. Assoc. Editor: John Clark.

J. Turbomach 141(3), 031015 (Feb 08, 2019) (12 pages) Paper No: TURBO-18-1096; doi: 10.1115/1.4041699 History: Received April 28, 2018; Revised October 06, 2018

A compressor blade integrated with circumferential groove casing treatment (CGCT) is optimized in this study. A hybrid aerodynamic optimization algorithm that combines the differential evolution (DE) with a radial basis function (RBF) response surface is used for the multi-objective optimization via the computational fluid dynamics (CFD) analysis. The sweep and lean distributions are optimized to pursue the maximum total pressure ratio and adiabatic efficiency at the design point. Constraints on the choking mass flow rate and the near-stall compression ratio are imposed to ensure the off-design performance. The performance is improved much more with the blade-CGCT integrated optimization than with the blade-only optimization. The stall margin of the blade-only optimized blade with CGCT added as an afterthought can be even worse than the baseline blade. The CGCT-removal test for the blade-CGCT integrated optimization result further verifies that the superior performance of the blade-CGCT integrated optimization is obtained via optimizing the coupling between the effects of the sweep and lean on the blade loading and the effects of the CGCT on the flow blockage.

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Fig. 1

Flow chart of the optimization

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Fig. 2

Illustration of the parameterization of the sweep and lean: (a) sweep and (b) lean

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Fig. 3

Structured mesh in the computational domain. (a) Geometry of the baseline rotor blade with five circumferential grooves installed on the casing; (b) side view of the grid distribution on the blade surface; (c) top view of the grid distribution in the blade tip; and (d) grid distribution near the leading edge of the blade tip.

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Fig. 4

Validation of the computational results: (a) total pressure ratio versus the mass flow rate; (b) the total temperature ratio versus the mass flow rate

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Fig. 5

Detailed framework of the hybrid optimization algorithm used in this study

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Fig. 6

Convergence histories of (a) the total pressure ratio and (b) the adiabatic efficiency for the two numerical optimizations (unfeasible individuals are removed)

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Fig. 7

Design point performance of the individuals in the two rounds of optimizations: (a) design objectives of all the qualified individuals; (b) design objectives of the two Pareto Fronts, three CGCT-add-on cases, and the baseline blade

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Fig. 8

Geometrical characteristics of blade P1 and blade P3: (a) blade geometry of P1; (b) blade geometry of P3; (c) sweep curves; (d) lean curves

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Fig. 9

Speed curves for the total pressure ratio of P1 and P3 with and without installing CGCT

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Fig. 10

Spanwise distribution of (a) the total pressure ratio, (b) the adiabatic efficiency at the design point (m = 9.67 kg/s), and (c) the diffusion factor at the near-stall point (m = 8.95 kg/s)

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Fig. 11

Flow separations in the root and the axial velocity contours on the axial slice near the trailing edge for the near-stall condition (m = 8.95 kg/s) (a) P1 and (b) P1_CGCT

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Fig. 12

Performance comparison between the two optimal individuals, P2 and Q1_CGCT, on the two Pareto Fronts. P2_CGCT is obtained by adding CGCT to P2; Q1 is obtained by removing CGCT from Q1_CGCT.

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Fig. 13

Geometrical characteristics of blade P2 and blade Q1: (a) blade geometry of P2; (b) blade geometry of Q1; (c) sweep distributions; (d) lean distributions

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Fig. 14

Speed curves for the total pressure ratio of P2 and Q1 with and without installing CGCT

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Fig. 15

Spanwise distribution of (a) the total pressure ratio and (b) the adiabatic efficiency at the design point (m = 9.67 kg/s)

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Fig. 16

Comparison of the dimensionless static pressure distributions at 93% and 80% span of blade P2 and Q1 with and without installing CGCT at the design point (m = 9.67 kg/s): (a) Ps/Ps,inlet at a 93% span; (b) Ps/Ps,inlet at an 80% span

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Fig. 17

At the design point (m = 9.67 kg/s), the relative Mach number contours on the blade-to-blade plane at 93% span of (a) P2; (b) P2_CGCT; (c) Q1; (d) Q1_CGCT



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