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Research Papers: Flows in Complex Systems

Experimental and Numerical Studies for a High Head Francis Turbine at Several Operating Points

[+] Author and Article Information
Chirag Trivedi

Ph.D. Student
Division of Fluid and Experimental Mechanics,
Department of Engineering
Sciences and Mathematics,
Lulea University of Technology,
Norrbotten 97187, Sweden;
Department of Mechanical and Industrial Engineering,
Indian Institute of Technology,
Roorkee 247667, India
e-mail: chirag.trivedi@ltu.se

Michel J. Cervantes

Professor
Division of Fluid and Experimental Mechanics,
Department of Engineering
Sciences and Mathematics,
Lulea University of Technology,
Norrbotten 97187, Sweden
e-mail: Michel.Cervantes@ltu.se

B. K. Gandhi

Professor
Department of Mechanical and Industrial Engineering,
Indian Institute of Technology,
Roorkee 247667, India
e-mail: bkgmefme@iitr.ernet.in

Ole G. Dahlhaug

Professor
Water Power Laboratory,
Department of Energy and Process Engineering,
Norwegian University of Science and Technology,
Trondheim 7491, Norway
e-mail: ole.g.dahlhaug@ntnu.no

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the Journal of Fluids Engineering. Manuscript received December 11, 2012; final manuscript received June 11, 2013; published online August 7, 2013. Assoc. Editor: Edward M. Bennett.

J. Fluids Eng 135(11), 111102 (Aug 07, 2013) (17 pages) Paper No: FE-12-1618; doi: 10.1115/1.4024805 History: Received December 11, 2012; Revised June 11, 2013

Experimental and numerical studies on a high head model Francis turbine were carried out over the entire range of turbine operation. A complete Hill diagram was constructed and pressure-time measurements were performed at several operating conditions over the entire range of power generation by installing pressure sensors in the rotating and stationary domains of the turbine. Unsteady numerical simulations were performed at five operating conditions using two turbulent models, shear stress transport (SST) k-ω and standard k-ε and two advection schemes, high resolution and second order upwind. There was a very small difference (0.85%) between the experimental and numerical hydraulic efficiencies at the best efficiency point (BEP); the maximum difference (14%) between the experimental and numerical efficiencies was found at lower discharge turbine operation. Investigation of both the numerical and experimental pressure-time signals showed that the complex interaction between the rotor and stator caused an output torque oscillation over a particular power generation range. The pressure oscillations that developed due to guide vanes and runner blades interaction propagate up to the trailing edge of the blades. Fourier analysis of the signals revealed the presence of a vortex rope in the draft tube during turbine operation away from the BEP.

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References

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Figures

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Fig. 1

Model Francis turbine test rig installed at the water power laboratory, NTNU

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Fig. 2

Locations of the pressure sensors and numerical points to record pressure-time data; positions VL01, P42, P71, S51, DT11, and DT21 were used for the experimental measurements

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Fig. 3

Computational domain of the model Francis turbine (ns = 0.27) with two interfaces namely distributer to runner (interface–I) and runner to draft tube (interface–II), 14 stay vanes, 28 guide vanes, runner with 15 full length blades and 15 splitters, and draft tube connected to runner outlet

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Fig. 4

Hexahedral mesh in the model Francis turbine along with conformal mesh at the interface–I

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Fig. 5

Pressure distribution on the blade for three grid densities and extrapolated pressure estimated using Eq. (11)

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Fig. 6

Hill diagram of the high head model Francis turbine (DM = 0.349 m, HM = 12 m): the vertical dotted line represents the operating conditions for the prototype turbine; circles represent the simulated operating conditions; bold lines represent regions with large torque oscillations

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Fig. 7

Standard deviation of the turbine output torque as a function of the speed factor (nED) and the guide vane angle at specific operating conditions; bold lines correspond to torque oscillations in the Hill diagram (Fig. 6)

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Fig. 8

Amplitudes of excitation frequencies at different turbine locations

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Fig. 9

Comparison of the experimental and numerical hydraulic efficiency of the turbine at five operating conditions

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Fig. 10

Comparison of experimental and numerical average pressure at different locations in the turbine (Q=0.07 m3s−1)

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Fig. 11

Comparison of experimental and numerical average pressure at different locations in the turbine (Q = 0.20 m3s−1)

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Fig. 12

Comparison of experimental and numerical average pressure at different locations in the turbine (Q = 0.22 m3s−1)

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Fig. 13

Experimental and numerical time-averaged pressure signal VL01 at a low discharge of 0.07 m3s−1; the circle at 228 deg represents the interaction of blade-22 and guide vane-8

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Fig. 14

Experimental and numerical time-averaged pressure signal VL01 at the BEP discharge of 0.20 m3s−1; the circle at 168 deg represents the interaction of blade-22 and guide vane-8

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Fig. 15

Experimental and numerical time-averaged pressure signals at VL01 for a high discharge of 0.22 m3s−1; the circle at 48 deg represents the interaction of guide vane-8 and blade-22

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Fig. 16

Experimental and numerical time-averaged pressure signal VL01 at the BEP discharge of 0.20 m3s−1; the circle at 168 deg represents the interaction of blade-22 and guide vane-8

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Fig. 17

Comparison of the experimental and numerical pressure-time signals at P42 for 0.22 m3s−1

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Fig. 18

Circumferential static pressure distribution in the stay vanes and guide vanes cascade before the runner inlet at high discharge operation, 0.22 m3s−1

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Fig. 19

Static pressure distribution on the blade surface at 0.22 m3s−1

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Fig. 20

Static pressure distribution on the blade surface at 0.07 m3s−1

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Fig. 21

Comparison of experimental and numerical pressure-time signals at P42 at 0.20 m3s−1

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Fig. 22

Static pressure distribution on the blade surface at the BEP for Q = 0.20 m3s−1

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Fig. 23

Effect of the RSI along the blade length on the pressure side of the blade during 12 deg angular movement of the runner at the BEP

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Fig. 24

Effect of the RSI along the blade length on the suction side of the blade during 12 deg angular movement of the runner at the BEP

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Fig. 25

Frequency spectrum of the numerical and experimental pressure-time domain signals at the BEP; the vertical scale is different in the two figures: (a) experimental, (b) numerical

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Fig. 26

Frequency spectrum of the numerical and experimental pressure-time domain signals at 0.07 m3s−1; the vertical scale is different in the two figures: (a) experimental, (b) numerical

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Fig. 27

Frequency spectrum of the numerical and experimental pressure-time domain signals at 0.22 m3s−1; the vertical scale is different in the two figures: (a) experimental, (b) numerical

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