Mach-number scaling of individual azimuthal modes of subsonic co-flowing jets

Sandberg, Richard D.; Tester, Brian J.

doi:10.1017/jfm.2016.133

Cited by 13 publications

(9 citation statements)

References 37 publications

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“…The flow is simulated with the compressible DNS code HiPSTAR, developed at the University of Southampton and recently used for a jet noise study (Sandberg & Tester 2016). A fourth-order central finite difference scheme with energy-conserving boundary schemes of the same order (Nordström & Carpenter 1998) is used in the longitudinal and the radial directions, while a pseudo-spectral method is used in the circumferential direction.…”

Section: Numerical Simulationmentioning

confidence: 99%

Self-similarity of fluid residence time statistics in a turbulent round jet

2017

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Fluid residence time is a key concept in the understanding and design of chemically reacting flows. In order to investigate how turbulent mixing affects the residence time distribution within a flow, this study examines statistics of fluid residence time from a direct numerical simulation (DNS) of a statistically stationary turbulent round jet with a jet Reynolds number of 7290. The residence time distribution in the flow is characterised by solving transport equations for the residence time of the jet fluid and for the jet fluid mass fraction. The product of the jet fluid residence time and the jet fluid mass fraction, referred to as the mass-weighted stream age, gives a quantity that has stationary statistics in the turbulent jet. Based on the observation that the statistics of the mass fraction and velocity are self-similar downstream of an initial development region, the transport equation for the jet fluid residence time is used to derive a model describing a self-similar profile for the mean of the mass-weighted stream age. The self-similar profile predicted is dependent on, but different from, the self-similar profiles for the mass fraction and the axial velocity. The DNS data confirm that the first four moments and the shape of the one-point probability density function of mass-weighted stream age are indeed self-similar, and that the model derived for the mean mass-weighted stream-age profile provides a useful approximation. Using the self-similar form of the moments and probability density functions presented it is therefore possible to estimate the local residence time distribution in a wide range of practical situations in which fluid is introduced by a high-Reynolds-number jet of fluid.

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Section: Numerical Simulationmentioning

confidence: 99%

Self-similarity of fluid residence time statistics in a turbulent round jet

2017

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“…The initial shear layers of the jet are turbulent and spreading in the radial direction, and then emerge at a distance about 12r 0 from the nozzle, where r 0 = d/2 is the radius of the jet nozzle. Figure 8b shows the instantaneous contours of dilation field ϑ = ∇ · u on the (z − x)-plane that qualitatively show the resulting acoustic radiation [44]. Section 2e highlights the connection and difference of equation (2.8) and the previous acoustic analogies.…”

Section: (C) Sound Generation By a Co-flowing Jetmentioning

confidence: 81%

A generalized sound extrapolation method for turbulent flows

Zhong¹,

Zhang²

2018

Proc. R. Soc. A.

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“…The turbulent jet flow with the co-flow jet Mach number M ∞ = 0.2 and the jet Mach number M j = 0.8 at Reynolds number Re = 8000 is studied with the established direct numerical simulation (DNS) data by Sandberg and Tester. 46 The sizes of the computational domain are 55 d and 40 d in the axial and radial directions, respectively, and d is the diameter of the jet nozzle. Figure 6 shows the instantaneous distribution of |∇ρ| and the illustration of the data collection surfaces for the computation of far-field directivities.…”

Section: Resultsmentioning

confidence: 99%

A comparison of acoustic far-field prediction methods for turbulent flows

Zhong

Zhang

Huang

2019

International Journal of Aeroacoustics

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Spurious wave contaminations may occur in the computations of acoustic far-field directivities in turbulent flows with only surface integrations. Two methods could be used to tackle the problem: (1) to take average of the solutions using multiple integration surfaces based on the Ffowcs-Williams and Hawkings equation that was widely applied to various aeroacoustics problems, and (2) to use the generalized sound extrapolation method based on an indirect acoustic variable to filter out the non-acoustic fluctuations in turbulent flows. The performances of the two methods are investigated by applying to the representative broadband airfoil leading edge noise and turbulent jet noise problems. For the Ffowcs-Williams and Hawkings approach, the prediction accuracy is sensitively influenced by the number and location of the integration surfaces. It often requires more than 10 well-configured surfaces to yield a convergent solution compare to the indirect acoustic variable method. The properties of robust and low computation cost of the indirect acoustic variable method suggest that it is potentially useful for the far-field computations of the aeroacoustics problems.

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Mach-number scaling of individual azimuthal modes of subsonic co-flowing jets

Cited by 13 publications

References 37 publications

Self-similarity of fluid residence time statistics in a turbulent round jet

Self-similarity of fluid residence time statistics in a turbulent round jet

A generalized sound extrapolation method for turbulent flows

A comparison of acoustic far-field prediction methods for turbulent flows

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