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Research Papers

Accounting for Uncontrolled Variations in Low-Speed Turbine Experiments

[+] Author and Article Information
Kathryn R. Evans

Whittle Laboratory,
University of Cambridge,
1 JJ Thomson Avenue,
Cambridge CB3 0DY, UK
e-mail: kathryn.evans@cantab.net

John P. Longley

Whittle Laboratory,
University of Cambridge,
1 JJ Thomson Avenue,
Cambridge CB3 0DY, UK
e-mail: jpl@eng.cam.ac.uk

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received September 1, 2016; final manuscript received March 9, 2017; published online May 9, 2017. Editor: Kenneth Hall.

J. Turbomach 139(10), 101005 (May 09, 2017) (12 pages) Paper No: TURBO-16-1222; doi: 10.1115/1.4036342 History: Received September 01, 2016; Revised March 09, 2017

It is common to assume that the performance of low-speed turbines depends only on the flow coefficient and Reynolds number. As such, the required operating point is achieved by controlling the values of these two nondimensional quantities by, for example, appropriate choices for the mass flow rate and applied brake torque. However, when the turbine has an atmospheric inlet and uses unconditioned air, variations in ambient pressure, temperature, and humidity are introduced. While it is still possible to maintain the required values for the flow coefficient and Reynolds number, the ambient variations affect additional nondimensional quantities which are related to the blade speed and gas properties. Generally, the values of these additional nondimensional quantities cannot be controlled and, consequently, they affect the turbine performance. In addition, thermal effects, which are exacerbated by the use of plastic blades, can cause changes in the blade row seal clearance and these also affect the performance. Therefore, to obtain measurements with greater accuracy and repeatability, the changes in the uncontrolled nondimensional quantities must be accounted. This paper contains four parts. First, it is described how suitable data acquisition parameters can be determined to eliminate short time scale facility unsteadiness within the measurements. Second, by the analysis of models, the most appropriate forms for the additional nondimensional quantities that influence turbine performance are obtained. Since the variations in the uncontrolled nondimensional quantities affect repeatability, the size of the effect on the turbine performance is quantified. Third, a best-fit accounting methodology is described, which reduces the effects of the uncontrolled nondimensional quantities on turbine performance, provided sufficient directly related measurements are available. Finally, the observations are generalized to high-speed turbomachines.

Copyright © 2017 by ASME
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References

Figures

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Fig. 1

Illustration of how an uncontrolled variation in the nondimensional quantity, b, can affect the turbine work coefficient, ψ. The mean values, ψ¯, of the two data families gives an incorrect result. By accounting to a common bdatum, the ψdatum values yield a reliable result.

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Fig. 2

Diagrams of the experimental facility: (a) schematic overview, (b) the working section (meridional view), and (c) circumferential positions of instrumentation (downstream view)

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Fig. 3

Reduction of the fractional noise in (a) flow coefficient and (b) Reynolds number, estimated assuming independent data and experimentally verified using multiple measurements

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Fig. 4

Fractional variation of (a) flow coefficient and (b) Reynolds number for the baseline experiments. Each experiment involves 600 1 s samples.

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Fig. 5

Variation of the measured turbine work coefficient for the baseline experiments (design ϕ and Re). Each experiment involves 600 1 s samples.

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Fig. 6

Variation of the mean value of quantities during baseline experiments: (a) nondimensional blade speed, (b) nondimensional gas expansion, and (c) nondimensional clearance

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Fig. 7

For the two-stage configuration, the effect of nondimensional blade speed on (a) the turbine work coefficient and (b) the axial velocities

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Fig. 8

The fractional variation of the turbine work coefficient calculated for the range of nondimensional blade speed during the experimental program

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Fig. 9

The fractional change of the turbine work coefficient calculated for the range of nondimensional gas expansion during the experimental program

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Fig. 10

The variation in c=gap/span for the range of facility temperature during the experimental program

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Fig. 11

Comparison of the measured unaccounted turbine work coefficient with the accounted values using the model and best-fit sensitivities

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Fig. 12

Measured and accounted variation of total-to-total efficiency with flow coefficient and Reynolds number; red = unaccounted, yellow = accounted

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Fig. 13

Spanwise profiles from the CFD calculations at double the experimental nondimensional blade speed compared with accounted profiles and measurements

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Fig. 14

Diagram showing the effect of the ambient conditions on the uncontrolled nondimensional quantities and the size of the effect on the turbine work coefficient during the experimental program

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Fig. 15

Control volume analysis to estimate the effect of gap/span on turbine performance

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