Research Papers

High Resolution Heat Transfer Measurements on the Stator Endwall of an Axial Turbine

[+] Author and Article Information
Benoit Laveau

Laboratory for Energy Conversion,
ETH Zurich,
Sonnegstrasse 3,
Zurich 8006, Switzerland
e-mail: blaveau@ethz.ch

Reza S. Abhari

Laboratory for Energy Conversion,
ETH Zurich,
Sonnegstrasse 3,
Zurich 8006, Switzerland
e-mail: rabhari@ethz.ch

Michael E. Crawford

Siemens Energy, Inc.,
4400 Alafaya Trail,
Orlando, FL 32826

Ewald Lutum

MTU Aero Engines AG,
Dachauer Strasse 665,
Munich D-80995, Germany

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received August 5, 2014; final manuscript received August 13, 2014; published online October 28, 2014. Editor: Ronald Bunker.The content of this paper is copyrighted by Siemens Energy, Inc. and is licensed to ASME for publication and distribution only. Any inquiries regarding permission to use the content of this paper, in whole or in part, for any purpose must be addressed to Siemens Energy, Inc. directly.

J. Turbomach 137(4), 041005 (Oct 28, 2014) (10 pages) Paper No: TURBO-14-1195; doi: 10.1115/1.4028431 History: Received August 05, 2014; Revised August 13, 2014

In order to continue increasing the efficiency of gas turbines, an important effort is made on the thermal management of the turbine stage. In particular, understanding and accurately estimating the thermal loads in a vane passage is of primary interest to engine designers looking to optimize the cooling requirements and ensure the integrity of the components. This paper focuses on the measurement of endwall heat transfer in a vane passage with a three-dimensional (3D) airfoil shape and cylindrical endwalls. It also presents a comparison with predictions performed using an in-house developed Reynolds-Averaged Navier–Stokes (RANS) solver featuring a specific treatment of the numerical smoothing using a flow adaptive scheme. The measurements have been performed in a steady state axial turbine facility on a novel platform developed for heat transfer measurements and integrated to the nozzle guide vane (NGV) row of the turbine. A quasi-isothermal boundary condition is used to obtain both the heat transfer coefficient and the adiabatic wall temperature within a single measurement day. The surface temperature is measured using infrared thermography through small view ports. The infrared camera is mounted on a robot arm with six degrees of freedom to provide high resolution surface temperature and a full coverage of the vane passage. The paper presents results from experiments with two different flow conditions obtained by varying the mass flow through the turbine: measurements at the design point (ReCax=7.2×105) and at a reduced mass flow rate (ReCax=5.2×105). The heat transfer quantities, namely the heat transfer coefficient and the adiabatic wall temperature, are derived from measurements at 14 different isothermal temperatures. The experimental data are supplemented with numerical predictions that are deduced from a set of adiabatic and diabatic simulations. In addition, the predicted flow field in the passage is used to highlight the link between the heat transfer patterns measured and the vortical structures present in the passage.

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Fig. 1

Secondary flow model by Langston [2]

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Fig. 2

Schematic view of the LISA research turbine test rig

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Fig. 3

3D geometry of the NGV (left) and predicted Mach number distribution at midspan

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Fig. 4

Test area in the turbine test rig. The camera is being traversed in front of the infrared transparent windows (highlighted) using the robot arm.

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Fig. 5

View of the hub endwall covered with Kapton through the opening between vanes

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Fig. 6

Cross section of the multilayer attached to the aluminum segment

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Fig. 7

Illustration of the linear fit procedure to deduce the heat transfer coefficient and the adiabatic wall temperature. Each best-fit line represents a different location in the passage shown in the bottom contour plot.

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Fig. 8

Top—thermal predictions of the temperature distribution below the multilayer. The dots highlight the positions of the temperature sensors embedded in the solid. Bottom—maximum temperature nonuniformity predicted across the passage.

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Fig. 9

Heat transfer coefficient relative uncertainty map

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Fig. 10

Nusselt number distribution in the passage in case 1: design point

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Fig. 11

Delta temperature between the total inlet temperature and the measured adiabatic wall temperature for case 1—design point

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Fig. 12

Nusselt number distribution in the passage in case 2: low mass flow

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Fig. 13

Data extracted along a streamline showing the repeatability of the measurement procedure. The error bar shows the ±10% uncertainty.

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Fig. 14

Location, label, and color codes of the streamlines along which the data are extracted for quantitative comparison shown in Figs. 13, 15, 18, and 19.

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Fig. 15

Comparison of the measured Nusselt number with established correlation for the corresponding incoming flow velocities. The error bars (±10%) are plotted for only one streamline per case. Fig. 14 provides the streamline locations.

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Fig. 16

Difference between total inlet temperature and adiabatic wall temperature predicted for case 1

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Fig. 17

Nusselt number distribution predicted for case 1

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Fig. 18

Comparison of measured and predicted temperature difference Tt,inTad along two streamlines for case 1. Figure 14 provides the streamlines locations.

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Fig. 19

Comparison of measured and predicted Nusselt number along two streamlines for case 1. Figure 14 provides the streamlines locations.

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Fig. 20

Superposition of streamlines highlighting the formation and the trajectory of the HV, and the Nusselt number contours




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