Jet near-field noise prediction

Harper-Bourne, Marcus

doi:10.2514/6.1999-1838

Cited by 24 publications

(24 citation statements)

References 4 publications

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“…One component u 2 1 in the downstream direction was experimentally investigated by Harper-Bourne. 17,18 He measured the decay of the coherence γ between the square of the axial velocity fluctuations u 2 1 in two axially displaced locations with hot-wire anemometry. The fixed location was located at x s /D = 4 and r s /D = 0.5.…”

Section: Iiie Simplification For a Cylindrical Source Regionmentioning

confidence: 99%

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On the Scaling of Jet Noise with Helmholtz Number Close to the Jet Axis

Michel

Ahuja

2014

20th AIAA/CEAS Aeroacoustics Conference

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Section: Iiie Simplification For a Cylindrical Source Regionmentioning

confidence: 99%

“…Any changes of the frequency spectra in the far field must be the result of source interference or wave propagation effects. The fixed-frame approach was also used by Harper-Bourne 17,18 and by Tam and Auriault. 19 This may be one explanation for the remarkable agreement of their jet-noise predictions with experimental data.…”

Section: Introductionmentioning

confidence: 99%

On the Scaling of Jet Noise with Helmholtz Number Close to the Jet Axis

Michel

Ahuja

2014

20th AIAA/CEAS Aeroacoustics Conference

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“…One of the most common methods for investigating the noise radiated by a jet flow is the determination of the source strength distribution along the jet axis. For single jet flows, this has been experimentally done by different techniques, using microphone phase array system and/or by using a highly directive microphone system like an elliptic mirror (Laufer et al, 1976;Fisher et al, 1977;Harper-Bourne, 1999).…”

Section: Introductionmentioning

confidence: 99%

Noise Source Distribution of Coaxial Subsonic Jet-Short-Cowl Nozzle

Almeida

Barbosa

Moro

et al. 2014

J.Aerosp. Technol. Manag.

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The noise source distribution of a short-cowl coaxial jet operating at different velocity ratios is described in this work. This was motivated by an ongoing research about noise prediction of coaxial jets through Acoustic Analogy with purposes of industrial engine application. This research has been carried out between Universidade Federal de Uberlândia (UFU), Brazil and the Institute of Sound and Vibration Research (ISVR) at Southampton University, UK. The numerical approach employed is originally based on Lighthill Acoustic Analogy. This technique, although likely known, is associated with an improved energy transfer timescale , used in the turbulence two-point correlation function, in order to enhance the source model. The source model is coupled with the aerodynamic calculation of flow through turbulence quantities evaluated by using a standard k-ε turbulence modeling. The Computational Fluid Dynamics data have also been used to provide complementary information about the coaxial jet noise production mechanisms. Experimental data were used in order to corroborate the results from the current model. Good agreement has been found, showing that high and low frequency contributors to the radiated noise for low velocity ratio are aggregated in a region about seven to ten secondary diameters downstream, while at higher velocity ratios sources are continuously spread from about one up to ten secondary diameters from the jet exit.

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“…Once we have obtained a general formulation, we construct a simple model for the jet source that is inspired by the work of Harper-Bourne [37]. An alternative source model based on steady Reynolds-averaged Navier-Stokes (RANS) solutions is developed in the Appendix.…”

mentioning

confidence: 99%

“…Comparisons of coherence between far-field observers and the measurement were satisfactory, but they most importantly illustrated the need to model the source as noncompact, even for jet far-field predictions. Harper-Bourne [37] developed semiempirical prediction methods for the acoustic loading from the jet near field on airframe structures. Semiempirical methods were developed based on a spatially varying source specified by array measurements.…”

mentioning

confidence: 99%

Prediction of Near-Field Jet Cross Spectra

Miller

2015

AIAA Journal

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A prediction method is developed based on the acoustic analogy for the cross-power spectral density in the convecting near field of compressible fluid turbulence. Equivalent source near-field, midfield, and far-field terms within the model integrand create corresponding near-field, midfield, and far-field radiating waves. These equivalent sources are modeled with a single equation for the two-point cross correlation of the Lighthill stress tensor that is dependent on the jet operating conditions. An alternative equivalent source model based on steady Reynoldsaveraged Navier-Stokes solutions is proposed. The cross-power spectral density model automatically reduces to a traditional autopower spectral density model when observers are at the same location. Predictions of radiation intensity and coherence compare favorably with measurements in the near field, midfield, and far field for a wide range of jet Mach numbers and temperature ratios.fully expanded jet diameter e s = number of ensembles F t = far-field integrand terms f = frequency G = cross-power spectral density g = Green's function k = turbulent kinetic energy l si = turbulent length scale M = Mach number M c = convective Mach number coefficient M d = design Mach number M j = fully expanded Mach number M t = midfield integrand terms M ∞;i = component of the vector freestream Mach number N t = near-field integrand terms P f = prefactor Pr = Prandtl number Pr t = turbulent Prandtl number p = pressure R = magnitude of x R g = gas constant R ijlm = two-point cross correlation of T ij r = source vector S = spectral density S ij = source tensor S y = equivalent spatial source distribution St = Strouhal number T ij = Lighthill stress tensor T j = fully expanded temperature t = time u = velocity vector u j = fully expanded jet velocity x = observer spatial coordinate y = source spatial coordinate y c = core length α = constant length scale coefficient β s= ratio of specific heats δ = Dirac delta function δ ij = Kronecker delta function ϵ = dissipation of turbulent kinetic energy ηξ; η; ζ = vector within source region ρ = density σ = anisotropic dependence parameter σ f = anisotropic amplification exponent τ = retarded time τ s = turbulent time scale ϕ = azimuthal observer angle Ψ = inlet observer angle ω = radial frequency

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Jet near-field noise prediction

Cited by 24 publications

References 4 publications

On the Scaling of Jet Noise with Helmholtz Number Close to the Jet Axis

On the Scaling of Jet Noise with Helmholtz Number Close to the Jet Axis

Noise Source Distribution of Coaxial Subsonic Jet-Short-Cowl Nozzle

Prediction of Near-Field Jet Cross Spectra

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