Identification of the formation of resonant tones in compressible cavity flows

Bacci, David; Saddington, Alistair J.; Bray, D.

doi:10.1016/j.ast.2018.03.013

Cited by 18 publications

(16 citation statements)

References 11 publications

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“…Strouhal numbers are typically associated with velocity fluctuations in the layers of the recirculating flow inside the cavity, whereas higher modes are associated with the formation of sub-eddies inside the stratified layers of the main inner vortex. The interaction of these centrifugal instabilities with the acoustic modes of the shear layer occur due to non-linear quadratic coupling, as shown in previous studies ( [5], [6], [8], [9]) and are responsible for the generation of the Rossiter-Heller tones.…”

Section: Introductionsupporting

confidence: 52%

“…This influenced the evolution of the main recirculatory vortex, and then its instabilities (directly correlated to ), and the shear layer trajectory (responsible for the feedback loop ). Previous studies [9] indicated that these phenomena are strongly non-linear, and minimal external influences could have been the cause of the high sensitivity of the associated central frequencies to even minimal local flow changes. The findings of this study are in line with previous works on the effect of incidence on weapons bay aeroacoustic response [22].…”

Section: Unsteady Flow Analysismentioning

confidence: 99%

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Exploring angle-of-attack effects in the aero-acoustic response of a weapons bay at transonic and supersonic Mach number

Bacci

2022

28th AIAA/CEAS Aeroacoustics 2022 Conference

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Numerical aero-acoustic analysis was conducted on a weapon bay model with doors, incorporating radar cross section reduction features. The effect of angle of attack on the aeroacoustic response of the cavity was analysed at a transonic Mach number of 0.85, and at a supersonic Mach number of 1.20. It was found that incidence had influence on both meanflow features and acoustic response. Further, linear and angular accelerations induced by the flow on doors revealed potential adverse fluid-structure coupling when results were compared with modal analysis. Again, angle of attack did influence the aeroacoustic effects on the cavity door structure.

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Section: Introductionsupporting

confidence: 52%

Section: Unsteady Flow Analysismentioning

confidence: 99%

Exploring angle-of-attack effects in the aero-acoustic response of a weapons bay at transonic and supersonic Mach number

Bacci

2022

28th AIAA/CEAS Aeroacoustics 2022 Conference

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“…For the time-frequency domain analysis, the Morlet wavelet transform was used to calculate the wavelet spectral power (WSP) map [27] where,…”

Section: Data Analysis Proceduresmentioning

confidence: 99%

“…For the characterisation of the statistical non-stationary modes the index of persistence (PR) was used [27]. This index varies from 0 %, indicating that a particular tone is inactive during the time window, to 100 %, indicating that a particular tone is always active during the time window.…”

Section: Data Analysis Proceduresmentioning

confidence: 99%

The effect of angle of attack on the aeroacoustic environment within the weapons bay of a generic UCAV

Bacci

Saddington

Bray

2019

Aerospace Science and Technology

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Cavity flow studies are generally concerned with observing the effect of geometry changes whilst maintaining a fixed zero angle of attack. Cavities employed as weapons bays will, however, experience a range of angles of attack. This paper presents the first known results showing the effect of flight angle of attack on the aeroacoustic characteristics of an internal weapons bay installed in an uninhabited combat air vehicle (UCAV). The UCAV geometry consisted of a Boeing M219-type cavity in a Boeing UCAV1303 airframe. Numerical simulation was conducted using a full-scale detached eddy simulation model and representative transonic flight conditions. As well as the reference case of zero degrees, data for angles of attack of 3.0, 4.5 and 6.0 degrees were analysed. Experimental data was used to validate the reference computational model, which agreed with the overall fluctuating sound pressure level (OAFPL) to within the experimental uncertainty of 4 dB. Data from the computational model was post-processed with frequency-domain and time-frequency-domain techniques showing that the flow structure within the weapons bay was altered significantly by the angle of attack changes, affecting the mean pressure distribution, frequency spectra and resonant modes. Overall, increasing the angle of attack from 0.0 to 3.0 degrees produced an increment in the acoustic load whilst a further increase tended to affect the resonance mechanism and thereby reduce the coherence and the temporal footprints of the resonant modes.

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“…Cavity flow oscillations exist in many aerospace engineering fields [1][2][3][4], such as weapon bays [5,6] and landing gears [7,8]. e physical mechanism in a cavity is complex.…”

Section: Introductionmentioning

confidence: 99%

Reduced‐Order Modeling of Cavity Flow Oscillations across Multi‐Mach Numbers Using Deep Learning

Liu

Ning

Ding

et al. 2021

Shock and Vibration

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The reduced-order model can accurately and efficiently predict unsteady problems in many aerospace engineering applications. The traditional reduced-order model based on proper orthogonal decomposition (POD) and Galerkin projection has poor robustness and large error in predicting complex problems. In this paper, a reduced-order model combining POD and deep learning is proposed to predict cavity flow oscillations under different flow conditions. Firstly, POD modes and corresponding coefficients are obtained by POD. Then, two deep learning frameworks, including multilayer perceptron (MLP) and long short-term memory (LSTM) neural networks, are used to predict the future POD coefficients, respectively. Finally, the cavity flow oscillations across multi-Mach numbers are predicted by the POD modes and the future coefficients. The results show that both of these frameworks can accurately predict cavity flow oscillations when the flow conditions change, and the time cost is reduced by order of magnitude. In addition, due to the performance of LSTM is better than that of MLP, its calculation speed is faster.

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Identification of the formation of resonant tones in compressible cavity flows

Cited by 18 publications

References 11 publications

Exploring angle-of-attack effects in the aero-acoustic response of a weapons bay at transonic and supersonic Mach number

Exploring angle-of-attack effects in the aero-acoustic response of a weapons bay at transonic and supersonic Mach number

The effect of angle of attack on the aeroacoustic environment within the weapons bay of a generic UCAV

Reduced‐Order Modeling of Cavity Flow Oscillations across Multi‐Mach Numbers Using Deep Learning

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