Identifying the dynamics underlying the large-scale and fine-scale jetnoise similarity spectra

Kerhervé, Franck; Guitton, Antoine; Jordan, Peter; Delville, J.; Fortuné, Véronique; Gervais, Yves; Tinney, Charles E.

doi:10.2514/6.2008-3027

Cited by 19 publications

(15 citation statements)

References 8 publications

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“…A Fourier filtering procedure for the separation of hydrodynamic and acoustic pressures in the near field was presented by Kerhervé et al (2008) and . Pseudo-sound and sound pressures were isolated on the basis of their phase velocity in the wavenumber-frequency spectrum.…”

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confidence: 99%

Wavelet decomposition of hydrodynamic and acoustic pressures in the near field of the jet

et al. 2017

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An experimental investigation of pressure fluctuations generated by a single-stream compressible jet is carried out in an anechoic wind tunnel. Measurements are performed using a linear array of microphones installed in the near region of the jet and a polar arc of microphones in the far field. The main focus of the paper is on the analysis of the pressure fluctuations in the near field. Three novel signal processing techniques are presented to provide the decomposition of the near-field pressure into hydrodynamic and acoustic components. The procedures are all based on the application of the wavelet transform to the measured pressure data and possess the distinctive property of requiring a very simple arrangement to obtain the desired results (one or two microphones at most). The hydrodynamic and acoustic pressures are characterized separately in terms of their spectral and statistical quantities and a direct link between the acoustic pressure extracted from the near field and the actual noise in the far field is established. The analysis of the separated pressure components sheds light on the nearly Gaussian nature/intermittent behaviour of the acoustic/hydrodynamic pressure. The higher sensitivity of the acoustic component to the Mach number variation has been highlighted as well as the different propagation velocities of the two pressure components. The achieved outcomes are validated through the application to the same data of existing separation procedures evidencing the advantages and limitations of the new methods

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confidence: 99%

Wavelet decomposition of hydrodynamic and acoustic pressures in the near field of the jet

et al. 2017

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“…16). Note that Kerherv e et al 17 proposed an inverse Strouhal number time scaling of the autocorrelation to account for differences in jet properties. However, because of the variation in peak frequency with position around the jet, the proposed peak-frequency scaling is more appropriate here to allow for the investigation of FSS and LSS radiation.…”

Section: Methodologies For Jet Noise Autocorrelation Analysismentioning

confidence: 99%

On autocorrelation analysis of jet noise

Harker

Gee

Neilsen

et al. 2013

The Journal of the Acoustical Society of America

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Meaningful use of the autocorrelation in jet noise analysis is examined. The effect of peak frequency on the autocorrelation function width is removed through a temporal scaling prior to making comparisons between measurements or drawing conclusions about source characteristics. In addition, a Hilbert transform-based autocorrelation envelope helps to define consistent characteristic time scales. Application of these processes to correlation functions based on large and fine-scale similarity spectra reveal that the large-scale noise radiation from an F-22A deviates from the similarity spectrum model.

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“…This confirms the finding of Refs. 52,54 for isothermal jets that the region of strongest noise production does not correspond to the region of highest turbulence intensity but is located closer to the jet axis. The main explanation for this phenomenon is that the convection velocity of turbulent structures closer to the centerline is higher, making them more efficient sound sources compared to turbulent structures in slower-moving fluid in the outer shear layer.…”

Section: Ivd Noise Generation Mechanisms In Heated Coaxial Jet Flowsmentioning

confidence: 97%

Flow Dynamics and Aeroacoustics of Heated Coaxial Jets at Subsonic Mach Numbers

Gloor

Buehler

Kleiser

2014

20th AIAA/CEAS Aeroacoustics Conference

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The flow field and the noise radiation of coaxial jet flows with a hot primary stream are investigated numerically by Large-Eddy Simulation and Direct Noise Computation (DNC). The core-stream velocity is subsonic based on local conditions but mostly supersonic with respect to the ambient speed of sound. The flow field and the associated acoustic radiation are analyzed systematically for a range of velocity and temperature ratios between the primary (core) and the secondary (bypass) stream. Strong mixing of cold and hot fluid and the intermittent character of the flow field close to the end of the potential core lead to a pronounced noise radiation at an aft angle of approximately 35 • . The unsteady pressure field within the jet flow is analyzed and radiating contributions are extracted using a Fourier-filtering technique. NomenclatureMach number Ma p,0 ≡ Ma 0 primary jet Mach number M a p,∞ = w * 0 /a * ∞ ambient Mach number (core) M a s,∞ = w * s /a * ∞ ambient Mach number (bypass) N number of grid points P power spectral density estimate p pressure ∆r, ∆θ, ∆z grid spacings ∆t simulation time step (r, θ, z) cylindrical coordinates R 1,2 primary / secondary jet radius r mic distance of virtual microphonesradial, azimuthal, axial velocity w 0 core-jet velocity z c length of potential core α axial wavenumber κ heat conductivity (ξ, η, ζ) computational coordinates µ dynamic viscosity ω circular frequency φ radiation angle ρ density Subscripts 0 reference quantity at r = z = 0 ∞ ambient conditions cl centerline quantity (r = 0) p primary (core) stream s secondary (bypass) stream rms root-mean-square Superscripts ′′ Favre fluctuation quantity b base flow * dimensional quantityConventions · temporal and azimuthal average

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Identifying the dynamics underlying the large-scale and fine-scale jetnoise similarity spectra

Cited by 19 publications

References 8 publications

Wavelet decomposition of hydrodynamic and acoustic pressures in the near field of the jet

Wavelet decomposition of hydrodynamic and acoustic pressures in the near field of the jet

On autocorrelation analysis of jet noise

Flow Dynamics and Aeroacoustics of Heated Coaxial Jets at Subsonic Mach Numbers

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