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Research Papers

Loads and Acoustics Prediction on Deployed Weapons Bay Doors

[+] Author and Article Information
Essam F. Sheta

CFD Research Corporation,
701 McMillian Way,
Huntsville, AL 35806
e-mail: essam.sheta@ngc.com

Robert E. Harris

CFD Research Corporation,
701 McMillian Way,
Huntsville, AL 35806
e-mail: reh@cfdrc.com

Benjamin George

Department of Mechanical and
Aerospace Engineering,
University of Florida,
Gainesville, FL 32611
e-mail: b.george@ufl.edu

Lawrence Ukeiley

Department of Mechanical and
Aerospace Engineering,
University of Florida,
Gainesville, FL 32611
e-mail: ukeiley@ufl.edu

Edward Luke

Department of Computer
Science and Engineering,
Mississippi State University,
Mississippi State, MS 39762
e-mail: luke@cse.msstate.edu

1Present address: Northrop Grumman Corporation, 1 Space Park, Manhattan Beach, CA 90266.

Contributed by the Noise Control and Acoustics Division of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received April 13, 2016; final manuscript received November 30, 2016; published online April 13, 2017. Assoc. Editor: Sheryl M. Grace.

J. Vib. Acoust 139(3), 031007 (Apr 13, 2017) (14 pages) Paper No: VIB-16-1174; doi: 10.1115/1.4035701 History: Received April 13, 2016; Revised November 30, 2016

Unsteady separated flow from deployed weapons bay doors can interact with the highly unsteady flow in the open bay cavity, which is known to exhibit strong acoustic content and could lead to fluid-resonance and high-intensity acoustic noise. The culmination of these unique flow physics can potentially excite structural modes of the doors, aircraft surfaces, or externally carried munitions and fuel tanks and can ultimately lead to aeroelastic instabilities, such as buffet, flutter, limit-cycle oscillations, or fatigue-induced failures. A hybrid Reynolds-averaged Navier–Stokes large eddy simulation (RANS/LES) method with low-dissipation schemes is developed to improve flow and acoustics predictive capabilities for supersonic weapons bays. Computational simulations are conducted for a weapons cavity with different deployed bay doors configurations, including the effect of dynamically moving doors, to assess the tonal content and unsteady aerodynamic loads on the doors. Wind tunnel testing is also carried out to provide unsteady experimental data for use in validating the high-fidelity simulation capability. The simulation results in terms of unsteady pressure, velocity fluctuations, and pressure resonant frequencies are computed and presented. The results suggest that the deployed doors energize the shear layer and cause it to go deeper into the cavity and produce higher unsteady fluctuations on the weapons cavity floor and aft wall. The deployed doors also cause a shift in the dominant resonant modes.

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References

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Figures

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Fig. 1

Supersonic wind tunnel at the University of Florida Fluid Mechanics Laboratory

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Fig. 2

Test section and cavity model with fully open deployed doors

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Fig. 3

Geometry and boundary conditions of the open cavity wind tunnel model

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Fig. 4

Cavity design with deployed doors: (a) leading-edge dimensions of the doors, (b) two fully open doors (90 deg), (c) two open doors (45 deg), and (d) one-open and one-closed door

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Fig. 5

Computational grid system inside and around the wind tunnel cavity model: (a) side view (z = 0) grid system, (b) front view (x/L = 0.5) grid system, and (c) top view (y/D = 0.5) grid system

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Fig. 6

Locations of pressure probe points on the cavity floor and aft wall

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Fig. 7

Effect of grid resolution on the fluctuating RMS pressure on the cavity floor

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Fig. 8

Aft wall center-point pressure spectrum compared with Rossiter prediction

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Fig. 9

Mean streamwise velocity (u/U) contours inside the cavity: (left) exp. and (right) CFD

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Fig. 10

Mean streamwise and turbulent velocity components at different streamwise sections along the cavity

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Fig. 11

Fluctuating RMS surface pressure on the cavity floor

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Fig. 12

Fluctuating RMS surface pressure on the cavity starboard open door

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Fig. 13

Fluctuating RMS surface pressure on the cavity 45 deg open doors

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Fig. 14

Fluctuating RMS and mean surface pressure on the cavity aft wall: (a) Prms and (b) Pmean

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Fig. 15

Experimental and computational fluctuating surface pressures on the cavity floor for multiple door configurations

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Fig. 16

Mean surface pressure on the cavity floor and port side wall: (a) no doors: floor, (b) open 90 deg doors: floor, (c) no doors: cavity port side, and (d) open 90 deg doors: cavity port side

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Fig. 17

Mean surface pressures at the middle section across the doors: (a) one door open, (b) 45 deg open doors, and (c) 90 deg open doors

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Fig. 18

Mean streamwise velocity contours inside the cavity: (a) no doors: u/U∞ and (b) 90 open doors: u/U∞

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Fig. 19

Mean turbulent eddy viscosity inside the cavity: (a) no doors: eddy viscosity and (b) 90 deg open doors: eddy viscosity

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Fig. 20

Fluctuating streamwise velocity components inside the cavity (y/D = −0.5): (a) no doors: RMS u/U∞, (b) 90 deg open doors: RMS u/U∞, (c) 45 deg open doors, and (d) one door open

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Fig. 21

Fluctuating streamwise velocity components at the middle section across the doors: (a) one door open, (b) 45 deg open doors, and (c) 90 deg open doors

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Fig. 22

Instantaneous snapshots of transient flow field components: (a) vorticity magnitude, (b) vorticity isosurface, and (c) surface pressure

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Fig. 23

Power spectra of the fluctuating surface pressure at the aft wall

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Fig. 24

Power spectra of the fluctuating surface pressure on the cavity floor: (a) x/L = 0.27 and (b) x/L = 0.73

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Fig. 25

Transient snapshots of surface pressure for dynamically moving cavity doors

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Fig. 26

Transient snapshots of surface pressure inside the cavity for dynamically moving doors

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Fig. 27

Fluctuating RMS surface pressure on the cavity floor for dynamically moving doors

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Fig. 28

Fluctuating RMS surface pressure on the cavity doors for dynamically moving doors: (a) port door and (b) starboard door

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