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Research Papers

On the Identification and Decomposition of the Unsteady Losses in a Turbine Cascade

[+] Author and Article Information
D. Lengani

DIME—Universitá di Genova,
Genova 16145, Italy
e-mail: davide.lengani@edu.unige.it

D. Simoni

DIME—Universitá di Genova,
Genova 16145, Italy
e-mail: daniele.simoni@unige.it

R. Pichler

University of Melbourne,
Melbourne 3010, Australia
e-mail: richard.pichler@unimelb.edu.au

R. D. Sandberg

University of Melbourne,
Melbourne 3010, Australia
e-mail: richard.sandberg@unimelb.edu.au

V. Michelassi

Baker Hughes, a GE Company,
Firenze 50127, Italy
e-mail: vittorio.michelassi@bhge.com

F. Bertini

AvioAero,
Torino 10040, Italy
e-mail: francesco.bertini@avioaero.it

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received September 19, 2018; final manuscript received November 29, 2018; published online January 16, 2019. Editor: Kenneth Hall.

J. Turbomach 141(3), 031005 (Jan 16, 2019) (10 pages) Paper No: TURBO-18-1252; doi: 10.1115/1.4042164 History: Received September 19, 2018; Revised November 29, 2018

The present paper describes the application of proper orthogonal decomposition (POD) to large eddy simulation (LES) of the T106A low-pressure-turbine profile with unsteady incoming wakes at two different flow conditions. Conventional data analysis applied to time averaged or phase-locked averaged flow fields is not always able to identify and quantify the different sources of losses in the unsteady flow field as they are able to isolate only the deterministic contribution. A newly developed procedure allows such identification of the unsteady loss contribution due to the migration of the incoming wakes, as well as to construct reduced order models that are able to highlight unsteady losses due to larger and/or smaller flow structures carried by the wakes in the different parts of the blade boundary layers. This enables a designer to identify the dominant modes (i.e., phenomena) responsible for loss, the associated generation mechanism, their dynamics, and spatial location. The procedure applied to the two cases shows that losses in the fore part of the blade suction side are basically unaffected by the flow unsteadiness, irrespective of the reduced frequency and the flow coefficient. On the other hand, in the rear part of the suction side, the unsteadiness contributes to losses prevalently due to the finer scale (higher order POD modes) embedded into the bulk of the incoming wake. The main difference between the two cases has been identified by the losses produced in the core flow region, where both the largest scale structures and the finer ones produces turbulence during migration. The decomposition into POD modes allows the quantification of this latter extra losses generated in the core flow region, providing further inputs to the designers for future optimization strategies.

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Figures

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Fig. 1

Scheme of the computational domain adopted for the postprocessing and integration areas

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Fig. 2

Contour plot of phase-averaged TKE and vectorial representation of phase-averaged perturbation velocity for three time snapshots: (a) 1B1 U case and (b) 1B3 U case

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Fig. 3

Cumulative contribution to TKE

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Fig. 4

Spectral analysis of the POD eigenvectors: (a) 1B1 U case and (b) 1B3 U case

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Fig. 5

Contour plot of TKE and vectorial representation of POD modes: (a) 1B1 U case and (b) 1B3 U case

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Fig. 6

Cumulative contribution to the production of TKE of different ranges of POD modes: modes related to the deterministic part of the passing wake (left column), modes related to the turbulence carried by the wakes and its interaction with the boundary layer (mid column), and modes related to the finer scale structures (right column): (a) 1B1 U case and (b) 1B3 U case

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Fig. 7

Cumulative contribution to the losses (entropy rate of change) of each POD mode. The values are obtained by integration over the 3D measurement domain. The plots are normalized by the total losses of the 1B3 U case.

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Fig. 8

Cumulative contribution to the losses in the boundary layers of each POD mode. The values are obtained by integration over the 3D measurement domain. The plots are normalized by the boundary layer losses of the 1B3 U case. Symbols indicate the viscous dissipation contribution.

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