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Research Papers: Flows in Complex Systems

Large-Eddy Simulation of Plasma-Based Active Control on Imperfectly Expanded Jets

[+] Author and Article Information
Kalyan Goparaju

Mem. ASME
Department of Mechanical and
Aerospace Engineering,
The Ohio State University,
Columbus, OH 43210
e-mail: goparaju.1@osu.edu

Datta V. Gaitonde

Professor
Fellow ASME
Department of Mechanical and
Aerospace Engineering,
The Ohio State University,
Columbus, OH 43210
e-mail: gaitonde.3@osu.edu

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received February 28, 2015; final manuscript received December 17, 2015; published online April 22, 2016. Assoc. Editor: Elias Balaras.

J. Fluids Eng 138(7), 071101 (Apr 22, 2016) (12 pages) Paper No: FE-15-1131; doi: 10.1115/1.4032571 History: Received February 28, 2015; Revised December 17, 2015

Jet flow control is important for mixing enhancement and noise mitigation. In previous efforts, we have used validated simulations to examine the effect of localized arc filament plasma actuators (LAFPA) on perfectly expanded Mach 1.3 jets. Here, we extend the analysis to an underexpanded jet at the same Mach number to examine the effect of shocks and expansions on control authority. After validation of the baseline flow, it is shown that the downstream evolution is relatively independent of Reynolds number. Simulations performed at different values of upstream pressure indicate that the higher stagnation pressure yields shock cells that are quantitatively stronger but qualitatively similar to those observed for the lower upstream stagnation pressure condition. For control simulations, axisymmetric mode pulsing is considered at two different Strouhal numbers of St = 0.3 and St = 0.9. These simulations show that the response of the jet to flow control is a strong function of the actuation frequency. Relative to the no-control case, actuating at the column-mode instability frequency (St = 0.3) results in an increase in the rate of spreading of the shear layer. Phase-averaged results indicate the formation of large toroidal vortices formed as a result of amplification of the column-mode instabilities that are excited at this frequency. On the other hand, the higher frequency actuation affects the initial shear-layer instability and interferes with the formation of the large-scale structures. Detailed integral azimuthal length scale analyses reveal that despite the absence of the axisymmetric toroids, the St = 0.9 case shows the dominance of the axisymmetric mode even at large distances from the nozzle exit. This indicates that flow control methods need not always have a visual signature of their influence on the system.

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Figures

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Fig. 1

Computational domain including the boundary conditions

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Fig. 2

Numerical model for actuators placed around the periphery at the nozzle exit

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Fig. 3

Comparison of centerline mean Mach number among different grids

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Fig. 4

Comparison of centerline urms among different grids

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Fig. 5

Comparison of experimental and numerical profiles of mean axial centerline velocity

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Fig. 6

Comparison of numerical and experimental contours of mean axial velocity

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Fig. 7

Contours of instantaneous Mach number for both Reynolds number cases: (a) high Reynolds number and (b) low Reynolds number

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Fig. 8

Comparison of centerline mean axial velocity for both the Reynolds number cases

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Fig. 9

Comparison of radial variation of mean axial velocity for both the Reynolds number cases at the nozzle exit

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Fig. 10

Comparison of axial variation of jet width between the Reynolds number cases

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Fig. 11

Contours of instantaneous Mach number for the control cases: (a) lower Strouhal number case (St = 0.3) and (b) higher Strouhal number case (St = 0.9)

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Fig. 12

Isolevels of instantaneous Q-criterion for the control cases: (a) lower Strouhal number case (St = 0.3) and (b) higher Strouhal number case (St = 0.9)

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Fig. 13

Comparison of radial variation of mean velocity at the nozzle exit

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Fig. 14

Comparison of radial variation of turbulence intensity between the baseline and the control cases at the nozzle exit

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Fig. 15

Comparison of centerline mean axial velocity for control cases

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Fig. 16

Comparison of variation of jet width with axial distance

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Fig. 17

Comparison of development of TKE along the jet centerline

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Fig. 18

Contours of phase-averaged vorticity magnitude for both control cases: (a) St = 0.3, phase 1 (ϕ = 0.1); (b) St = 0.9, phase 1 (ϕ = 0.1); (c) St = 0.3, phase 4 (ϕ = 0.6); and (d) St = 0.9, phase 4 (ϕ = 0.6)

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Fig. 19

Isolevels of phase-averaged Q-criterion for the St = 0.3 case

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Fig. 20

Isolevels of phase-averaged Q-criterion for the St = 0.9 case

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Fig. 21

Comparison of axial variation of L-parameter among different cases

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Fig. 22

Azimuthal decomposition for the baseline case

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Fig. 23

Azimuthal decomposition for the St = 0.3 case

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Fig. 24

Azimuthal decomposition for the St = 0.9 case

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Fig. 25

Comparison of centerline mean axial velocity for cases without control employing different values of upstream pressure

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Fig. 26

Comparison of centerline mean axial velocity for cases with control employing different values of upstream pressure

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Fig. 27

Isolevels of Q-criterion for the St = 0.3 case for different values of upstream pressure: (a) LTP condition, phase 1 (ϕ = 0.1) and (b) HTP condition, phase 1 (ϕ = 0.1)

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