Research Papers

Experimental Measurements of Gas Turbine Flow Capacity Using a Novel Transient Technique

[+] Author and Article Information
T. Povey

Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK

M. Sharpe, A. Rawlinson

Turbine Sub-systems, Rolls-Royce PLC, Moor Lane, Derby, DE24 8BJ, UK

J. Turbomach 133(1), 011005 (Sep 07, 2010) (15 pages) doi:10.1115/1.4000481 History: Received April 07, 2008; Revised February 20, 2009; Published September 07, 2010; Online September 07, 2010

Nozzle guide vane (NGV) flow capacity is perhaps the most important parameter for engine optimization. Inaccurate evaluation of capacity would lead to incorrect performance evaluation, and unmatched stages. A new semi-transient technique has been developed and demonstrated that will allow turbine designers to measure experimentally the effective throat area of an annular cascade of nozzle guide vanes at engine-representative Mach number, Reynolds number, and mainstream-to-cooling-flow pressure ratio. The technique allows NGV capacity to be measured to bias and precision uncertainties to 95% confidence of ±0.546% and ±0.028%, which compares well to large scale industrial facilities. Order-of-magnitude cost savings are offered over typical continuously running industrial facilities by running in blowdown mode from a receiver tank, thus removing the need for large scale compressor plant. To demonstrate the technique, a high mass flow rate blowdown tunnel was developed and commissioned at the University of Oxford, and the capacity of a high-pressure NGV from a large civil aircraft engine was experimentally determined. Experimental results are presented, which allow the precision error to be accurately calculated. A detailed uncertainty analysis is given from which the bias error is computed. It is shown that the low precision error the new technique offers means that it is ideally suited to investigations in which secondary influences on capacity are the subject of the investigation. The technique is of industrial significance because methods to compute engine capacity analytically or computationally do not yet provide sufficient accuracy for engine optimization, and the new technique offers equivalent accuracy at a much reduced cost over conventional experimental techniques. By performing an uncertainty analysis using experimental data it is shown that the increase in uncertainty due to the semi-transient (as opposed to steady state) nature of the technique is approximately 0.004% (to 95% confidence), and is entirely negligible. The experimentally measured trend of capacity against pressure ratio is compared with simple 1D, 2D, and 3D inviscid models, and an analytical correction for total pressure loss is performed. It is shown that while a simple 3D model is better than a 1D model (up to 1.5% improvement) for crude estimates of engine capacity, experimental trends are poorly predicted by such simple techniques. An analytical correction for total pressure loss increases the difference between 3D prediction and experiment. The experimental data demonstrate the complex nature of the process by which nozzle capacity is determined and the need for accurate, low-cost experimental techniques for capacity measurement. Correction to engine conditions is discussed.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

Isentropic capacity as a function of p2/p01

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Figure 2

Mach number contours for the two cascades (modified from Ref. 4); M=1 is shown as bold

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Figure 3

Capacity trends for the two cascades (modified from Ref. 4)

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Figure 4

Flow schematic of the facility

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Figure 5

Schematic of the working section

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Figure 6

The working section of the facility viewed from downstream

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Figure 7

NGV pressure ratio for different limiter sizes A1

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Figure 8

Coolant capacity versus coolant-to-mainstream pressure ratio

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Figure 9

Typical pressures during a blowdown run

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Figure 10

Coolant-to-mainstream pressure ratio

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Figure 11

Typical temperatures during a blowdown run

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Figure 12

Mass flow rates during a typical run

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Figure 13

Vane pressure ratios as measured on the hub and case platforms

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Figure 14

Pressure distribution on a NGV platform at t=10 s and 25 s

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Figure 15

Capacity as a function of the mean vane pressure ratio

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Figure 16

Capacity as measured in 17 runs

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Figure 17

Standard deviation and standard error in mean

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Figure 18

Reynolds number versus exit Mach number for 17 runs

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Figure 19

Mean measured hub and case pressures as functions of the mean pressure ratio

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Figure 20

Pressure field for a 3D isentropic calculation

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Figure 21

Comparison of 1D, 2D, 3D, and experimental trends

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Figure 22

Schematic of the test vane and CNC measurement planes

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Figure 23

Comparison of measured capacity against capacity predicted using measured geometric throat area

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Figure 24

Unsteady correction terms for each of the plena for a typical run

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Figure 25

Sensitivity of capacity to pressure ratio




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