An Acoustic Source Modeling Technique to Predict the Near Sound Field of Axisymmetric Turbulent Jets (original) (raw)
Related papers
Acoustic Sources and Far-Field Noise of Chevron and Round Jets
AIAA Journal, 2015
This paper investigates numerically the acoustic sources and far-field noise of chevron and round jets. The acoustic sources are described by the fourth-order space-time velocity cross-correlations which are calculated based on a Large Eddy Simulation (LES) flowfield. Gaussian functions are found to fit the axial, radial and azimuthal cross-correlations reasonably well. The axial length scales are 3-4 times the radial and azimuthal length scales. For the chevron jet, the cross-correlation scales vary with azimuthal angle up to 6 jet diameters downstream; beyond that, they become axisymmetric like those for a round jet. The fourth-order space-time cross-correlation of the axial velocity, R 1111 , is the dominant source component and there are considerable contributions from other source components such as R 2222 , R 3333 , R 1212 , R 1313 and R 2323 cross-correlations where 1, 2 and 3 represent axial, radial and azimuthal directions respectively. For the chevron jet, these cross-correlations decay rapidly with axial distance whereas, for the round jet, they remain roughly constant over the first 10 jet diameters. The chevron jet intensifies both the R 2222 and R 3333 crosscorrelations within 2 jet diameters of the jet exit. The amplitude, length and time scales of the cross-correlations of a LES velocity field are investigated as functions of position and are found to be proportional to the turbulence amplitude, length and time scales that are determined from a Reynolds Averaged Navier-Stokes (RANS) calculation. The constants of proportionality are found to be independent of position within the jet and they are quite close for chevron and round jets. The scales derived from RANS are used for source description and an acoustic analogy is used for * Corresponding author; AIAA Member; Email: nkd25@cam.ac.uk 1 of 43 sound propagation. There is an excellent agreement between the far-field noise predictions and measurements. At low-frequencies, the chevron nozzle significantly reduces the far-field noise by 5-6 dB at 30 0 and 2-3 dB at 90 0 to the jet axis. However, the chevron nozzle slightly increases highfrequency noise. It was found that R 1212 and R 1313 cross-correlations have the largest contribution to the jet noise at 30 0 to the jet axis whereas, the R 2323 cross-correlation has the largest contribution to the jet noise at 90 0 to the jet axis. The RANS calculations are repeated with different turbulence models and the noise prediction is found to be almost insensitive to the turbulence model. The results indicate that the modelling approach is capable of assessing advanced noise-reduction concepts. Nomenclature A Amplitude scale, m 4 /s 4 d Distance from the wall, m d c RANS cut-off distance, m G k Turbulent production, m 2 /s 3 h Enthalpy, m 2 /s 2 k Turbulent kinetic energy, m 2 /s 2 l Length scale, m p Pressure, N/m 2 Q Source term, kg/(m-s 3 ) R ijkl Fourth-order space-time cross-correlations, m 4 /s 4 T ij Source term, kg/(m-s 2 ) v Mean axial velocity, m/s y Source location, m µ Dynamic viscosity, kg/(m-s) µ t Turbulent viscosity, kg/(m-s) τ Time shift, s τ s Time scale, s ξ Spatial separation, m ρ Mean density, kg/m 3 Turbulent dissipation rate, m 2 /s 3 ( ) Time averaging ( ) Favre averaging 2 of 43 4 of 43
arXiv (Cornell University), 2019
This paper uses asymptotic analysis within the generalized acoustic analogy formulation (Goldstein. JFM 488, pp. 315-333, 2003) to develop a noise prediction model for the peak sound of axisymmetric round jets at subsonic acoustic Mach numbers (M a). The analogy shows that the exact formula for the acoustic pressure is given by a convolution product of a propagator tensor (determined by the vector Green's function of the adjoint linearized Euler equations for a given jet mean flow) and a generalized source term representing the jet turbulence field. Using a low frequency/small spread rate asymptotic expansion of the propagator, mean flow nonparallelism enters the lowest order Green's function solution via the streamwise component of the mean flow advection vector in a hyperbolic partial differential equation (PDE). We then address the predictive capability of the solution to this PDE when used in the analogy through first-of-its-kind numerical calculations when an experimentally-verified model of the turbulence source structure is used together with Reynolds-averaged Navier Stokes solutions for the jet mean flow. Our noise predictions show a reasonable level of accuracy in the peak noise direction at M a = 0.9, for Strouhal number up to about 0.6, and at M a = 0.5 using modified source coefficients. Possible reasons for this are discussed. Moreover, the prediction range can be extended beyond unity Strouhal number by using an approximate composite asymptotic formula for the vector Green's function that reduces to the locally parallel flow limit at high frequencies.
Identification of Sound Sources in Large-Eddy Simulations of Jets
13th AIAA/CEAS Aeroacoustics Conference (28th AIAA Aeroacoustics Conference), 2007
in two studies, one aimed at spatially locating the sources of the noise radiated in a particular direction and frequency, and the other at estimating the transmission of noise from a turbulent region through another turbulent region. The first study is based on the integrands on a Ffowcs Williams-Hawkings surface placed as close as possible to the mixing layers, and on expressing the sound intensity as an integral that assigns a contribution to each point on the surface. Both steps are plausible, but not exact, and this is discussed in detail. The outcome conforms to expectations, for instance in attributing high-frequency noise to the mixing layer, more precisely to the part which faces the observer, and closer to the nozzle the higher the frequency is. In the second study, artificial monopole sources are added to an LES, and their sound tracked both in the near-field and far-field. Sources are placed in the potential core, as well as in the mixing layer and outside the jet with various locations relative to the observer. Simple refraction theory based on the mean flow field and assuming full conservation of wave action is quite successful, both in terms of wave-fronts and sound level, even at a diameter Strouhal number St of only 1. The principal difference is that theory predicts an abrupt cone of silence, which LES does not.
Prediction of jet mixing noise with Lighthill's Acoustic Analogy and geometrical acoustics
The Journal of the Acoustical Society of America
A computational aeroacoustics prediction tool based on the application of Lighthill's theory is presented to compute noise from subsonic turbulent jets. The sources of sound are modeled by expressing Lighthill's source term as two-point correlations of the velocity fluctuations and the sound refraction effects are taken into account by a ray tracing methodology. Both the source and refraction models use the flow information collected from a solution of the Reynolds-Averaged Navier-Stokes equations with a standard k-epsilon turbulence model. By adopting the ray tracing method to compute the refraction effects a high-frequency approximation is implied, while no assumption about the mean flow is needed, enabling the authors AQ3 to apply the new method to jet noise problems with AQ4 inherently three-dimensional propagation effects. Predictions show good agreement with narrowband measurements for the overall sound pressure levels and spectrum shape in polar angles between 60 and 110 for isothermal and hot jets with acoustic Mach number ranging from 0.5 to 1.0. The method presented herein can be applied as a relatively low cost and robust engineering tool for industrial optimization purposes. V
Turbulent jet flow noise prediction
The text of the abstract follows. In this paper we describe a numerical approach to completely determine the structure of a low Reynolds number compressible jet o w and to compute the associated sound waves in the far eld. The method is applied to simulate a Reynolds number 4; 000, Mach number 0:8 jet, with the results validated by comparison with the jet reproduced experimentally. The mean o w and far eld sound results are shown to while matching conditions are created experimentally inside a low pressure tank. The mean o w results of the DNS are seen to correspond well with our experimental results, and to be compatible with those published in the literature. The semi-analytically obtained sound eld is shown to be identical to that obtained purely by the DNS in the near eld, while in the far eld matches those obtained by us experimentally, and compatible with experimental results previously published.
Prediction of Turbulence-Generated Noise in Unheated Jets
The model-based approach, used by the JeNo code to predict jet noise spectral directivity, is described. A linearized form of Lilley's equation governs the non-causal Green s function of interest, with the non-linear terms on the right hand side identified as the source. A Reynolds-averaged Navier-Stokes (RANS) solution yields the required mean flow for the solution of the propagation Green s function in a locally parallel flow. The RANS solution also produces time- and length-scales needed to model the non-compact source, the turbulent velocity correlation tensor, with exponential temporal and spatial functions. It is shown that while an exact non-causal Green s function accurately predicts the observed shift in the location of the spectrum peak with angle as well as the angularity of sound at low to moderate Mach numbers, the polar directivity of radiated sound is not entirely captured by this Green s function at high subsonic and supersonic acoustic Mach numbers. Results pres...
Journal of Fluid Mechanics, 2012
Five isothermal round jets at Mach number M = 0.9 and Reynolds number Re D = 10 5 originating from a pipe nozzle are computed by large-eddy simulations to investigate the effects of initial turbulence on flow development and noise generation. In the pipe, the boundary layers are untripped in the first case and tripped numerically in the four others in order to obtain, at the exit, mean velocity profiles similar to a Blasius laminar profile of momentum thickness equal to 1.8 % of the jet radius, yielding Reynolds number Re θ = 900, and peak turbulence levels u ′ e around 0, 3 %, 6 %, 9 % or 12 % of the jet velocity u j . As the initial turbulence intensity increases, the shear layers develop more slowly with much lower root-mean-square (r.m.s.) fluctuating velocities, and the jet potential cores are longer. Velocity disturbances downstream of the nozzle exit also exhibit different structural characteristics. For low u ′ e /u j , they are dominated by the first azimuthal modes n θ = 0, 1 and 2, and show significant skewness and intermittency. The growth of linear instability waves and a first stage of vortex pairings occur in the shear layers for u ′ e /u j 6 %. For higher u ′ e /u j , threedimensional features and high azimuthal modes prevail, in particular close to the nozzle exit where the wavenumbers naturally found in turbulent wall-bounded flows clearly appear. Concerning the sound fields, strong broadband components mainly associated with mode n θ = 1 are noticed around the pairing frequency for the untripped jet. With rising u ′ e /u j , however, they become weaker, and the noise levels decrease asymptotically down to those measured for jets at Re D 5 × 10 5 , which are likely to be initially turbulent and to emit negligible vortex-pairing noise. These results correspond well to experimental observations, made separately for either mixing layers, jet flow or sound fields.
The Properties and Localizations of Acoustic Sources of High Speed Jet
AIAA SciTech, 53rd AIAA Aerospace Sciences Meeting, 2015
Jet noise has become one major concern for aircraft engine design in recent decades. The problem is to identify the near-field (NF) structures that produce far-field (FF) noise in order to improve noise control and reduction strategies. An algorithm has been developed to identify the events that are captured by several signals simultaneously in both NF and FF. In this paper, we attempt to improve the reliability of a previously devised algorithm that looks for main contributors to NF-FF correlations. 1,2 We focus on one set of experimental data from Mach 0.6 jet. It consists of 10kHz TRPIV measurement and pressure sampling in both NF and FF. Q criterion signals at different NF locations are compared with FF Microphone signals inside the cone of coherence. The potential events extracted are interpretted as part of the large coherent structures that correlate with the FF. In the time-frequency domain, the events are short wave packets, distorted by ambient perturbations. The algorithm is tested by synthetic signals which are composed of Morlet wave packets and background noise. The NF localization and time sequencing of these potential event clusters are compared to another two lists of event candidates.