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Research Papers: Flows in Complex Systems

Physical Explanation of the Hysteresis in Wells Turbines: A Critical Reconsideration

[+] Author and Article Information
Tiziano Ghisu

Assistant Professor
Department of Mechanical,
Chemical and Materials Engineering,
University of Cagliari,
Cagliari 09123, Italy
e-mail: t.ghisu@unica.it

Pierpaolo Puddu

Professor
Department of Mechanical,
Chemical and Materials Engineering,
University of Cagliari,
Cagliari 09123, Italy
e-mail: pierpaolo.puddu@dimcm.unica.it

Francesco Cambuli

Assistant Professor
Department of Mechanical,
Chemical and Materials Engineering,
University of Cagliari,
Cagliari 09123, Italy
e-mail: cambuli.f@unica.it

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received December 7, 2015; final manuscript received March 15, 2016; published online July 15, 2016. Assoc. Editor: Kwang-Yong Kim.

J. Fluids Eng 138(11), 111105 (Jul 15, 2016) (9 pages) Paper No: FE-15-1895; doi: 10.1115/1.4033320 History: Received December 07, 2015; Revised March 15, 2016

The hysteretic behavior of Wells turbines is a well-recognized phenomenon. As it appears at nondimensional frequencies orders of magnitude lower than the ones studied in rapidly pitching airfoils and wings, the cause is likely to be different. Some authors found its origin in the interaction between secondary flow structures and trailing edge vortices. In this work, a detailed numerical analysis of the performance of a Wells turbine submitted to a sinusoidal bidirectional flow is presented. Computational results are compared with experimental data available from literature and suggest a new explanation of the phenomenon.

Copyright © 2016 by ASME
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Figures

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Fig. 1

Computational domain, simplified geometry

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Fig. 2

Computational domain, full geometry

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Fig. 3

Computational mesh for the moving reference frame: (a) blade and hub surface mesh and (b) close-up view of the hub

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Fig. 4

Steady simulations (six-blade configuration, σt = 0.57)

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Fig. 5

Influence of time step size in transient simulations: (a) Δt = 2 × 10−2 s, (b) Δt = 5 × 10−3 s, and (c) Δt = 1.25 × 10–3 s

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Fig. 6

Comparison between experimental and computational results (six-blade turbine, σt = 0.57)

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Fig. 7

Computational performance as a function of local flow variables (six-blade turbine, σt = 0.57)

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Fig. 8

Local flow coefficient ϕl as a function of flow coefficient ϕ (six-blade turbine, σt = 0.57)

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Fig. 9

Spanwise distribution of axial velocity during acceleration and deceleration, for the same values of flow coefficient ϕ, during outflow: (a) ϕ=0.09 and (b) ϕ=0.18

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Fig. 10

Spanwise distribution of axial velocity during acceleration and deceleration, for equal inlet mass-flows, during outflow: (a) ϕl=0.096 and (b) ϕl=0.214

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Fig. 11

Midspan pressure coefficient distributions during acceleration and deceleration, for the same values of flow coefficient ϕ (left) and for the same values of local flow coefficient ϕl (right), during outflow: (a) ϕ=0.09, (b) ϕl=0.096, (c) ϕ=0.18, and (d) ϕl=0.214

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Fig. 12

Comparison of nondimensionalized relative velocity contours during acceleration (left) and deceleration (right), at different radial positions (r*): (a) ϕl=0.096 and (b) ϕl=0.214

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Fig. 13

Nondimensionalized tangential vorticity contours at ϕl=0.096 during acceleration (left) and during deceleration (right), at planes with different tangential positions: (a) 35% chord, (b) 70% chord, and (c) 90% chord

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Fig. 14

Nondimensionalized tangential vorticity contours at ϕl=0.214 during acceleration (left) and during deceleration (right), at planes with different tangential positions: (a) 35% chord, (b) 70% chord, and (c) 90% chord

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Fig. 15

Pathlines near the blade suction side during acceleration (left) and deceleration (right) for the six-blade turbine, σt = 0.57, for different values of ϕl : (a) ϕl=0.096 and (b) ϕl=0.214.

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Fig. 16

Comparison between experimental and computational results (five-blade turbine, σt = 0.48)

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Fig. 17

Comparison between experimental and computational results (seven-blade turbine, σt = 0.67)

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Fig. 18

Local flow coefficient ϕl as a function of flow coefficient ϕ (five- and seven-blade turbines, σt = 0.48 and σt = 0.67)

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Fig. 19

Computational performance as a function of local flow variables (five-blade turbine, σt = 0.48)

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Fig. 20

Computational performance as a function of local flow variables (seven-blade turbine, σt = 0.67)

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