Research Papers

High-Fidelity Simulations of Low-Pressure Turbines: Effect of Flow Coefficient and Reduced Frequency on Losses

[+] Author and Article Information
V. Michelassi

General Electric Global Research,
Garching bei München D-85748, Germany
e-mail: vittorio.michelassi@ge.com

L. Chen, R. Pichler, R. Sandberg

Aerodynamics and Flight Mechanics
Research Group, Faculty of Engineering
and the Environment,
University of Southampton,
Southampton SO17 1BJ, UK

R. Bhaskaran

General Electric Global Research,
Niskayuna 12309, NY

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received February 10, 2016; final manuscript received March 1, 2016; published online May 17, 2016. Editor: Kenneth C. Hall.

J. Turbomach 138(11), 111006 (May 17, 2016) (12 pages) Paper No: TURBO-16-1041; doi: 10.1115/1.4033266 History: Received February 10, 2016; Revised March 01, 2016

Large eddy simulations validated with the aid of direct numerical simulation (DNS) are used to study the concerted action of reduced frequency and flow coefficient on the performance of the T106A low-pressure turbine profile. The simulations are carried out by using a discretization in space and time that allows minimizing the accuracy loss with respect to DNS. The reference Reynolds number is 100,000, while reduced frequency and flow coefficient cover a range wide enough to provide valid qualitative information to designers. The various configurations reveal differences in the loss generation mechanism that blends steady and unsteady boundary layer losses with unsteady wake ingestion losses. Large values of the flow coefficient can alter the pressure side unsteadiness and the consequent loss generation. Low values of the flow coefficient are associated with wake fogging and reduced unsteadiness around the blade. The reduced frequency further modulates these effects. The simulations also reveal a clear trend of losses with the wake path, discussed by conducting a loss-breakdown analysis that distinguishes boundary layer from wake distortion losses.

Copyright © 2016 by ASME
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Fig. 1

Computational domain and block decomposition

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Fig. 2

DNS and LES of bar wakes (section 1, left) and turbine profile wakes (section 2, right), Cp (bottom)

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Fig. 3

Mass-averaged inlet and exit flow angles

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Fig. 4

Phase-lock averaged turbulent kinetic energy snapshots for the eight LES cases

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Fig. 5

Minimum and maximum velocity across two sections (left column: x = −0.05 and right column x = 0.95) for eight combinations of Φ, Fred

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Fig. 6

Minimum and maximum turbulent kinetic energy across two sections (left column: x = −0.05 and right column x = 0.95) for eight combinations of Φ, Fred

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Fig. 7

Space–time plot of LES wall shear stress and comparison with DNS time-averaged wall shear stress, 2B1U

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Fig. 8

Kinetic loss profiles 1.26% chord downstream of the trailing edge for the eight LES

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Fig. 9

Minimum, average, and maximum normalized pressure from phase-lock averages for 1B1U and 1B3U

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Fig. 10

Top: LES and DNS mixed-out loss, ωM, as function of reduced frequency for different flow coefficients. Bottom: wake distortion losses, ωwake.

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Fig. 11

Top: control-volume based profile losses from Denton. Bottom: contribution from each of the three terms.

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Fig. 12

Difference between mixed-out and control-volume losses

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Fig. 13

Top: definition of Lw/C and Gw/C. Bottom: Gw/C and Lw/C trends.

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Fig. 14

Mixed-out losses as a function of Lw/C and Gw/C

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Fig. 15

Top: wake distortion losses. Bottom: mixed-out to control-volume losses deviation.




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