Research Papers

A Particle Image Velocimetry-Based Investigation of the Flow Field in an Oblique Jet Impingement Configuration

[+] Author and Article Information
Sebastian Schulz

e-mail: sebastian.schulz@itlr.uni-stuttgart.de

Simon Schueren

e-mail: simon.schueren@itlr.uni-stuttgart.de

Jens von Wolfersdorf

e-mail: itljvw@itlr.uni-stuttgart.de
Institute of Aerospace Thermodynamics,
University of Stuttgart,
Pfaffenwaldring 31,
Stuttgart 70569, Germany

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received July 1, 2013; final manuscript received July 17, 2013; published online September 27, 2013. Editor: Ronald Bunker.

J. Turbomach 136(5), 051009 (Sep 27, 2013) (10 pages) Paper No: TURBO-13-1121; doi: 10.1115/1.4025212 History: Received July 01, 2013; Revised July 17, 2013

Impinging jets have become an indispensable measure for cooling applications in gas turbine technology. The present study seeks to explore the flow field dynamics inside an enigine-relevant cooling passage of trapezoidal cross-section. The investigated geometry produces a highly complex flow field which was investigated employing particle image velocimetry (PIV). The experiments were accompanied by numerical simulations solving the Reynolds-averaged Navier–Stokes (RANS) equations with FLUENT using the low-Re k-ω-SST (shear stress transport) turbulence model. Additionally, time-resolved pressure measurements were performed utilizing Kulite pressure transducers. The spectral analysis of the transient pressure signal in conjunction with a proper orthogonal decomposition (POD) analysis of the PIV data allows for a detailed insight into the effects of geometric constraints on the fluid dynamic processes inside the geometry. The results are presented for a jet Reynolds number of 45,000 and display a qualitatively fair agreement between the experiments and numerical simulations. Nevertheless, the simulations predict flow features in particular regions of the geometry that are absent in the experiments. Despite the lack of conspicuous high energy modes, the flow was well suited for a POD analysis. Depending on the considered PIV plane, it could be shown that up to 25% of the flow field's total turbulent energy is contained in the first ten POD modes. Additionally, using the first 20 to 60 POD modes sufficed to reconstruct the flow fields with its governing features.

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Fig. 1

Concept for an impingement cooled midchord passage of a turbine blade, based upon Ref. [22]

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Fig. 2

Schematic of the experimental facility

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Fig. 3

Schematic of the test geometry

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Fig. 4

Illustration of the PIV measurement arrangement

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Fig. 5

Pressure tap locations for static and time-resolved measurements

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Fig. 7

Time-averaged velocity fields: (a), (c), and (e) experiment, and (b), (d), and (f) CFD

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Fig. 8

Vorticity magnitude: (a), (c), and (e) experiment, and (b), (d), and (f) CFD; the circle denotes the core impingement

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Fig. 9

Turbulent kinetic energy based on in-plane fluctuations

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Fig. 10

POD eigenvalue spectra for the investigated planes of this study

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Fig. 11

Spatial projection of the POD basis function for different modes in different planes

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Fig. 12

Examples of a PIV snapshot and its POD-filtered equivalent for each plane, displaying: (a), (d), and (g) the original velocity field; (b), (e), and (h) the swirling strength; and (c), (f), and (i) the vorticity magnitude

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Fig. 13

Examples of the POD filtered flow field from the jets of rows (a) A1, and (b) A2 in the xz-plane

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Fig. 14

Normalized pressure distribution along wall C considering the jet flow provided by rows A1 and A2

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Fig. 15

Single-sided power spectrum at distinct locations on wall C considering the jet flow provided by rows A1 and A2




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