Analysis of unsteady supersonic cavity flow employing an adaptive meshing algorithm

Zhang, Xin; Edwards, J. A.

doi:10.1016/0045-7930(95)00045-3

Cited by 27 publications

(14 citation statements)

References 15 publications

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“…21 At the selected inflow conditions, the interaction of the shear layer with the rear bulkhead sets up a feed-back loop that self-sustains the instability. The cavity flow dynamics is dominated by the motion of large scale flow structures [22][23][24] and features strong indications of a limit-cycle instability. These structures are the energy containing eddies in the shear layer and are the main drivers of the self-sustained flow unsteadiness.…”

Section: -20mentioning

confidence: 99%

“…These structures are the energy containing eddies in the shear layer and are the main drivers of the self-sustained flow unsteadiness. Past numerical work [23][24][25][26] has shown that these structures can be modelled successfully by an appropriate time-dependent two-dimensional numerical method. This method resolves directly in space and time the large-scale motion in the flow and uses a turbulence model to account for the effects of the unresolved scales of motion on the macro-dynamics of the flow.…”

Section: -20mentioning

confidence: 99%

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Control of Transonic Cavity Flow Instability by Streamwise Air Injection

Rona

2004

42nd AIAA Aerospace Sciences Meeting and Exhibit

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A time-dependent numerical model of a turbulent Mach 1.5 flow over a rectangular cavity has been developed, to investigate suppression strategies for its natural self-sustained instability. This instability adversely affects the cavity form drag, it produces largeamplitude pressure oscillations in the enclosure and it is a source of far-field acoustic radiation.To suppress the natural flow instability, the leading edge of the two-dimensional cavity model is fitted with a simulated air jet that discharges in the downstream direction. The jet mass flow rate and nozzle depth are adjusted to attenuate the instability while minimising the control mass flow rate.The numerical predictions indicate that, at the selected inflow conditions, the configurations with the deepest nozzle (0.75 of the cavity depth) give the most attenuation of the modelled instability, which is dominated by the cavity second mode. The jet affects both the unsteady pressure field and the vorticity distribution inside the enclosure, which are, together, key determinants of the cavity leading instability mode amplitude. The unsteadiness of the pressure field is reduced by the lifting of the cavity shear layer at the rear end above the trailing edge. This disrupts the formation of upstream travelling feed-back pressure waves and the generation of far-field noise. The deep nozzle also promotes a downstream bulk flow in the enclosure, running from the upstream vertical wall to the downstream one. This flow attenuates the large-scale clockwise recirculation that is present in the unsuppressed cavity flow. The same flow alters the top shear layer vorticity thickness and probably affects the convective growth of the shear layer cavity second mode.

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Section: -20mentioning

confidence: 99%

Section: -20mentioning

confidence: 99%

Control of Transonic Cavity Flow Instability by Streamwise Air Injection

Rona

2004

42nd AIAA Aerospace Sciences Meeting and Exhibit

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“…At this regime, limit-cycle self-sustained instabilities may be encountered [18][19][20] that require a non-linear modelling approach. Specifically, a Proper Orthogonal Decomposition (POD) of the flow [21][22][23] is used to qualify the dynamic system in the enclosure.…”

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confidence: 99%

“…24 The interaction of the shear layer with the rear bulkhead is part of a feed-back loop which self-sustains the instability. This configuration was studied experimentally at Cambridge 25 and then further numerical work was conducted at the University of Southampton, 19,20,26 leading to benchmark data to develop the reduced order dynamic model that is presented in this paper. Other flow regimes and geometries have been investigated independently and a useful collection of such work is given by Grace.…”

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confidence: 99%

“…These instabilities are the energy containing eddies in the shear layer and were found to be the main drivers of the self-sustained flow unsteadiness. 19,20,26 The use of active controllers to suppress the cavity flow instability and minimise pressure fluctuations requires the implementation of control devices. In order to design practicable, implementable real-time feedback controllers, it is necessary to have a control device that is computationally efficient.…”

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confidence: 99%

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POD Analysis of Cavity Flow Instability

Rona

Brooksbank

2003

41st Aerospace Sciences Meeting and Exhibit

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A Mach 1.5 turbulent cavity flow develops largeamplitude oscillations, pressure drag and noise. This type of flow instability affects practical engineering applications, such as aircraft store bays. A simple model of the flow instability is sought towards developing a real-time model-based active control system for simple geometries, representative of open aircraft store bays.An explicit time marching second-order accurate finite-volume scheme has been used to generate timedependent benchmark cavity flow data. Then, a simpler and leaner numerical predictor for the unsteady cavity pressure was developed, based on a Proper Orthogonal Decomposition of the benchmark data.The low order predictor gives pressure oscillations in good agreement with the benchmark CFD method. This result highlights the importance of large-scale phase-coherent structures in the Mach 1.5 turbulent cavity flow. At the selected test conditions, the significant pressure 'energy' content of these structures enabled an effective reduced order model of the cavity dynamic system. Directions and methods to further streamline and simplify the unsteady pressure predictor have been highlighted.

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Analysis of two dimensional and three dimensional supersonic turbulence flow around tandem cavities

Woo

Lee

2006

J Mech Sci Technol

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Analysis of unsteady supersonic cavity flow employing an adaptive meshing algorithm

Cited by 27 publications

References 15 publications

Control of Transonic Cavity Flow Instability by Streamwise Air Injection

Control of Transonic Cavity Flow Instability by Streamwise Air Injection

POD Analysis of Cavity Flow Instability

Analysis of two dimensional and three dimensional supersonic turbulence flow around tandem cavities

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