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Research Papers

Comprehensive Geometric Description of Manufacturing Scatter of High-Pressure Turbine Nozzle Guide Vanes for Probabilistic CFD Analysis

[+] Author and Article Information
Paul Voigt

Chair of Turbomachinery and Flight Propulsion,
Institute of Fluid Mechanics,
Technische Universität Dresden,
D-01062 Dresden, Germany
e-mail: paul.voigt@tu-dresden.de

Lars Högner, Barbara Fiedler, Matthias Voigt, Ronald Mailach

Chair of Turbomachinery and Flight Propulsion,
Institute of Fluid Mechanics,
Technische Universität Dresden,
D-01062 Dresden, Germany

Marcus Meyer

Rolls-Royce Deutschland Ltd & Co KG, CFD Methods,
D-15827 Blankenfelde-Mahlow, Germany

Alkin Nasuf

GWT-TUD GmbH,
D-01307 Dresden, Germany

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the Journal of Turbomachinery. Manuscript received February 1, 2019; final manuscript received February 14, 2019; published online March 2, 2019. Assoc. Editor: Kenneth Hall.

J. Turbomach 141(8), 081002 (Mar 02, 2019) (8 pages) Paper No: TURBO-19-1025; doi: 10.1115/1.4042892 History: Received February 01, 2019; Accepted February 14, 2019

The increasing demands on jet engines require progressive thermodynamic process parameters, which typically lead to higher aerothermal loadings and accordingly to designs with high complexity. State-of-the-art high-pressure turbine (HPT) nozzle guide vane (NGV) design involves vane profiles with three-dimensional features including a high amount of film cooling and profiled endwalls (PEWs). Typically, the specific mass flow, also called capacity, which governs the engine's operation, is set by the HPT NGV. Hence, geometric variations due to manufacturing scatter of the HPT NGV's passage can affect relevant aerodynamic quantities and the entire engine behavior. Within the traditional deterministic design approach, the influences of those geometric variations are covered by conservative assumptions and engineering experience. This paper addresses the consideration of variability due to the manufacturing of HPT NGVs through probabilistic CFD investigations. To establish a statistical database, 80 HPT NGVs are digitized with a high precision optical 3D scanning system to record the outer geometry. The vane profiles are parametrized by a section-based approach. For this purpose, traditional profile theory is combined with a novel method that enables the description of NGV profile variability taking the particular leading edge (LE) shape into account. Furthermore, the geometric variability of PEWs is incorporated by means of principle component analysis (PCA). On this basis, a probabilistic system assessment including a sensitivity analysis in terms of capacity and total pressure loss coefficient is realized. Sampling-based methods are applied to conduct a variety of 3D CFD simulations for a typical population of profile and endwall geometries. This probabilistic investigation using realistic input parameter distributions and correlations contributes to a robust NGV design in terms of relevant aerodynamic quantities.

Copyright © 2019 by Rolls-Royce plc
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References

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Figures

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Fig. 1

Removal of cooling holes: (a) BladeCleaner input and (b) BladeCleaner output

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Fig. 2

Profile section processing: (a) section extraction and (b) camber line

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Fig. 3

TE-Slot parameter definition

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Fig. 4

Segmentation and parametrization of closed profile section: (a) segmentation of profile section and (b) remaining airfoil parameters

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Fig. 5

Typical thickness and camber distribution for a closed NGV profile section

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Fig. 6

Parametrization of NGV LE shape

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Fig. 7

Kernel density estimation of xΨ,LE−PSP1

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Fig. 8

Correlation matrix of the profile 1 parameters

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Fig. 9

Effect of mode 1 for hub PEW (top) and shroud PEW (bottom)

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Fig. 10

Scatter fraction and partial fraction of HUB PEW eigenvalues

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Fig. 11

Manufacturing scatter (top, scan to cad; bottom left, scan to median model) and parametric rebuild accuracy (bottom right, scan to rebuild)

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Fig. 12

Schematic procedure of sampling-based uncertainty quantification

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Fig. 13

CFD Domain and TE-area mesh details: (a) CFD domain and (b) TE-area mesh details

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Fig. 14

Histogram of relative capacity and pressure loss coefficient change: (a) capacity and (b) pressure loss coefficient

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Fig. 15

Capacity sensitivity: (a) Spearman correlation coefficient r~ and (b) coefficient of importance CoI

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Fig. 16

Throat area aspect ratio

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