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Research Papers: Flows in Complex Systems

Numerical Modeling of Stall and Poststall Events of a Single Pitching Blade of a Cycloidal Rotor

[+] Author and Article Information
Kuldeep Singh

Department of Electromechanical Engineering,
University of Beira Interior,
R. Marquês D'Avila e Bolama,
Covilhã 6201-001, Portugal
e-mail: k.singh@ubi.pt

José Carlos Páscoa

Associate Professor
Department of Electromechanical Engineering,
University of Beira Interior,
R. Marquês D'Avila e Bolama,
Covilhã 6201-001, Portugal
e-mail: pascoa@ubi.pt

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received January 26, 2018; final manuscript received May 10, 2018; published online June 27, 2018. Assoc. Editor: Philipp Epple.

J. Fluids Eng 141(1), 011103 (Jun 27, 2018) (16 pages) Paper No: FE-18-1056; doi: 10.1115/1.4040302 History: Received January 26, 2018; Revised May 10, 2018

In the present work, a numerical study is carried out to compare the performance of seven turbulence models on a single pitching blade of cycloidal rotor operating in deep dynamic stall regime at moderate Reynolds number. The investigated turbulence models were: (i) kω-shear stress transport (SST), (ii) kω-SST with γ, (iii) transition SST (γ–Reθ), (iv) scale adaptive simulation (SAS), (v) SAS coupled with transition SST, (vi) SAS with γ, and (vii) detached eddy simulation (DES) coupled with transition kω-SST. The wake vortices evolution and shedding analysis are also carried out for the pitching blade. The performance of the investigated turbulence models is evaluated at various critical points on the hysterias loop of lift and drag coefficients. The predictions of the investigated turbulence models are in good agreement at lower angle of attack, i.e., αu ≤ 20 deg. The detailed quantitative analysis at critical points showed that the predictions of SAS and transition SST-SAS turbulence models are in better agreement with the experimental results as compared to the other investigated models. The wake vortices analysis and fast Fourier transport analysis showed that the wake vortex characteristics of a pitching blade are significantly different than those for the low amplitude oscillating blade at the higher reduced frequency.

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Figures

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Fig. 2

(a) Computational domain, (b) dynamic mesh zone, and (c) blade pitching arrangement

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Fig. 1

Schematic diagram of cycloidal rotor with pitching blade

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Fig. 3

(a) A typical grid close to blade surface and (b) wall y+ on the blade

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Fig. 4

Grid dependence study using SST- turbulence model at Re = 1.35 × 105: (a) lift coefficient and (b) drag coefficient

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Fig. 5

Time dependence study using SST- turbulence model at Re = 1.35 × 105

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Fig. 6

Comparison of ((a) and (b)) lift and drag coefficient obtained from (SST- model) with corresponding experimental results of Lee and Gerontakos [13], numerical results (SST- model) of Wang et al. [27], Comparison of ((c) and (d)) nondimensional velocity in the normal direction to the axis of blade for upstroke angles 22 deg and 24 deg with the experimental results of Wernert et al. [12] and numerical results of Spentzos et al. [23]

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Fig. 7

Comparison of numerical results for ((a) and (b)) lift coefficient at ① formation of LEV (αu ≈ 12 deg) ② spread of flow reversal (αu ≈ 21 deg) ③ turbulent break-down (αu ≈ 22 deg) ④ stall (αu ≈ 24 deg) ⑤ end of stall (αd ≈ 24.5 deg) ⑥ formation of secondary vortex (αd ≈ 24.9 deg) ⑦ beginning of flow re-attachment (αd ≈ 14 deg) ⑧ fully re-attached flow (αd ≈ 1 deg) and ((c) and (d)) drag coefficient obtained from SAS and transition SST-SAS turbulence models at ① formation of LEV (αu ≈ 12 deg) ② drag coefficient cross-over (αu ≈ 17 deg) ③ turbulent break-down (αu ≈ 22 deg) ④ stall (αu ≈ 24 deg) ⑤ end of stall (αd ≈ 24.5 deg)

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Fig. 10

Q-contour chronology using SAS turbulence model

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Fig. 11

Q-contour chronology using turbulence model SST coupled with SAS

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Fig. 8

Intermittency-contour chronology using transition SST and transition SST-SAS turbulence models

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Fig. 9

Variation of skin friction coefficient for -SST-γ-Reθ turbulence model ((a) and (b)) and transition SST-SAS turbulence model ((c) and (d)) at various angles of attack

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Fig. 12

Velocity in wake region

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Fig. 13

Nondimensionalized z-vorticity contours of wake region at various angles of attack for SAS turbulence model

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Fig. 14

Fast Fourier transformation analysis of wake vortices at various locations for (a) SAS turbulence model and (b) SST-SAS turbulence model

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