Jittering Wave-Packet Models for Subsonic Jet Noise

Cavalieri, André V. G.; Jordan, Peter; Agarwal, Anurag; Gervais, Yves

doi:10.2514/6.2010-3957

Cited by 52 publications

(97 citation statements)

References 24 publications

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“…At (t + t ray c o /D) = 165 and (t + t ray c o /D) = 165.3 they become axially organized and axisymmetric, with a hydrodynamic pressure field comprising three high-amplitude spatial oscillations, consistent with the preferred structure of Hussain & Zaman (1981), the near-field signatures observed by in co-axial jets, and the wavepackets identified experimentally and numerically, respectively by Cavalieri et al (2011aCavalieri et al ( , 2012b, as being associated with the low-angle axisymmetric component of jet noise. It appears to be this energization of the axisymmetric component of the flow that underpins the high-amplitude burst, the temporal growth and decay being particularly important, consistent with the simplified models of Sandham et al (2006) and Cavalieri et al (2011b). Figure 12 allows an analysis over a longer period of time, where many such bursts are observed.…”

Section: Source Mechanism Analysismentioning

confidence: 58%

“…However, it is not possible to provide a precise definition of what is meant by coherent structures, nor is there general agreement as to which aspects of their motion lead to the directive sound field produced by the round jet; see reviews of Jordan & Gervais (2008) and Jordan & Colonius (2013) and the introduction of Cavalieri et al (2011b) for further discussion). The tool presented here is intended to provide clarification on this point.…”

Section: Computing the Sound-producing Flow Skeletonq Dmentioning

confidence: 97%

“…Following a methodology similar to that of Cavalieri et al (2010Cavalieri et al ( , 2011b and Koenig et al (2011), a wavelet transform is used in order to identify temporally localized, high-amplitude fluctuations in the low-angle sound emission; those fluctuations are then tracked back into the conditional flow field to discern the flow behaviour that led to their emission. The continuous wavelet transform involves a projection of the pressure signal onto a set of basis functions that are localized in both time and time scale, being thus better adapted to the analysis of intermittent events than the Fourier basis.…”

Section: Source Mechanism Analysismentioning

confidence: 99%

“…With a view to obtaining an approximation of the axisymmetric component of the sound field, known to dominate downstream radiation (Michalke & Fuchs 1975;Fuchs & Michel 1978;Juvé, Sunyach & Comte-Bellot 1980;Cavalieri et al 2011b), the pressure signals used in the stochastic estimation are obtained by averaging the upper and lower sections of Ω A :…”

Section: Linear Stochastic Estimationmentioning

confidence: 99%

“…Papers studying the kinds of wavepacket behaviour that can lead to sound generation (wavepacket-to-sound arrow) include Crighton & Huerre (1990) and Sandham, Morfey & Hu (2006), but these papers do not include any comprehensive comparisons with data. Cavalieri et al (2011b) explore how the details of time-local wavepacket dynamics can impact the sound field: this work involves quantitative comparison with LES data. Reba, Narayanan & Colonius (2010) have coupled near-field data, via a kinematic model of the wavepacket fluctuations registered on a Kirchhoff surface, to the far field.…”

Section: Introductionmentioning

confidence: 99%

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Educing the source mechanism associated with downstream radiation in subsonic jets

et al. 2012

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This work belongs to the ongoing debate surrounding the mechanism responsible for low-angle sound emission from subsonic jets. The flow, simulated by large eddy simulation (Bogey & Bailly, Comput. Fluids, vol. 35 (10), 2006a, pp. 1344-1358, is a Mach 0.9 jet with Reynolds number, based on the exit diameter, of 4 × 10 5 . A methodology is implemented to educe, explore and model the flow motions associated with low-angle sound radiation. The eduction procedure, which is based on frequency-wavenumber filtering of the sound field and subsequent conditional analysis of the turbulent jet, provides access to space-and time-dependent (hydrodynamic) pressure and velocity fields. Analysis of these shows the low-angle sound emission to be underpinned by dynamics comprising space and time modulation of axially coherent wavepackets: temporally localized energization of wavepackets is observed to be correlated with the generation of high-amplitude acoustic bursts. Quantitative validation is provided by means of a simplified line-source Ansatz (Cavalieri et al. J. Sound Vib., vol. 330, 2011b, pp. 4474-4492). The dynamic nature of the educed field is then assessed using linear stability theory (LST). The educed pressure and velocity fields are found to compare well with LST: the radial structures of these match the corresponding LST eigenfunctions; the axial evolutions of their fluctuation energy are consistent with the LST amplification rates; and the relative amplitudes of the pressure and velocity fluctuations, which are educed independently of one another, are consistent with LST.

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Section: Source Mechanism Analysismentioning

confidence: 58%

Section: Computing the Sound-producing Flow Skeletonq Dmentioning

confidence: 97%

Section: Source Mechanism Analysismentioning

confidence: 99%

Section: Linear Stochastic Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Educing the source mechanism associated with downstream radiation in subsonic jets

et al. 2012

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Analysis techniques for aeroacoustics: noise source identification

Jordan

2013

Noise Sources in Turbulent Shear Flows: Fundamentals and Applications

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A high-fidelity method to analyze perturbation evolution in turbulent flows

Nair

Gaitonde

2016

Journal of Computational Physics

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Small perturbation propagation in fluid flows is usually examined by linearizing the governing equations about a steady basic state. It is often useful, however, to study perturbation evolution in the unsteady evolving turbulent environment. Such analyses can elucidate the role of perturbations in the generation of coherent structures or the production of noise from jet turbulence. The appropriate equations are still the linearized Navier-Stokes equations, except that the linearization must be performed about the instantaneous evolving turbulent state, which forms the coefficients of the linearized equations. This is a far more difficult problem since in addition to the turbulent state, its rate of change and the perturbation field are all required at each instant. In this paper, we develop and use a novel technique for this problem by using a pair (denoted "baseline" and "twin") of simultaneous synchronized Large-Eddy Simulations (LES). At each time-step, small disturbances whose propagation characteristics are to be studied, are introduced into the twin through a forcing term. At subsequent time steps, the difference between the two simulations is shown to be equivalent to solving the forced Navier-Stokes equations, linearized about the instantaneous turbulent state. The technique does not put constraints on the forcing, which could be arbitrary, e.g., white noise or other stochastic variants. We consider, however, "native" forcing having properties of disturbances that exist naturally in the turbulent environment. The method then isolates the effect of turbulence in a particular region on the rest of the field, which is useful in the study of noise source localization. The synchronized technique is relatively simple to implement into existing codes. In addition to minimizing the storage and retrieval of large time-varying datasets, it avoids the need to explicitly linearize the governing equations, which can be a very complicated task for viscous terms or turbulence closures. The method is illustrated by application to a well-validated Mach 1.3 jet. Specifically, the effects of turbulence on the jet lipline and core collapse regions on the near-acoustic fields are isolated. The properties of the method, including linearity and effect of initial transients, are discussed. The results provide insight into how turbulence from different parts of the jet contribute to the observed dominance of low and high frequency content at shallow and sideline angles, respectively.

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Jittering Wave-Packet Models for Subsonic Jet Noise

Cited by 52 publications

References 24 publications

Educing the source mechanism associated with downstream radiation in subsonic jets

Educing the source mechanism associated with downstream radiation in subsonic jets

Analysis techniques for aeroacoustics: noise source identification

A high-fidelity method to analyze perturbation evolution in turbulent flows

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