Simulation and measurement of flow generated noise

Moore, Peter; Slot, Harmen; Boersma, Bendiks Jan

doi:10.1016/j.jcp.2007.04.006

Cited by 9 publications

(7 citation statements)

References 15 publications

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“…6, the potential core is estimated to end near x/D=7. This value compares well with values found in literature of potential core lengths of jets with similar jet conditions [21,29]. The measurements indicate the jet to have a centreline decay constant B u = 5·6 which is in accordance with values found in literature [3,36].…”

Section: Mean Flow Fieldsupporting

confidence: 92%

“…Inherent to computing limitations, a Direct Numerical Simulation (DNS) of a compressible jet flow is commonly performed on high Mach number jets with a low Reynolds number such as the DNS of Freund [10] and Moore et al [21]. Before jet flow or jet noise predictions based on a DNS of a turbulent flow can be relied upon, the numerical work need be carefully validated by means of detailed and reliable experimental evidence.…”

Section: Introductionmentioning

confidence: 99%

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Experiments on the Flow Field and Acoustic Properties of a Mach number 0·75 Turbulent Air Jet at a Low Reynolds Number

Slot

Moore

Delfos

et al. 2009

Flow Turbulence Combust

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In this paper we present the experimental results of a detailed investigation of the flow and acoustic properties of a turbulent jet with Mach number 0·75 and Reynolds number 3·5 10 3 . We describe the methods and experimental procedures followed during the measurements, and subsequently present the flow field and acoustic field. The experiment presented here is designed to provide accurate and reliable data for validation of Direct Numerical Simulations of the same flow. Mean Mach number surveys provide detailed information on the centreline mean Mach number distribution, radial development of the mean Mach number and the evolution of the jet mixing layer thickness both downstream and in the early stages of jet development. Exit conditions are documented by measuring the mean Mach number profile immediately above the nozzle exit. The fluctuating flow field is characterised by means of a hot-wire, which produced radial profiles of axial turbulence at several stations along the jet axis and the development of flow fluctuations through the jet mixing layer. The axial growth rate of the jet instabilities are determined as function of Strouhal number, and the axial development of several spectral components is documented. The directivity of the overall sound pressure level and several spectral components were investigated. The spectral content of the acoustic far field is shown to be compatible with findings of hot-wire experiments in the mixing layer of the jet. In addition, the measured acoustic spectra agree with Tam's large-scale similarity and fine-scale similarity spectra (Tam et al., AIAA Pap 96, 1996).

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Section: Mean Flow Fieldsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Experiments on the Flow Field and Acoustic Properties of a Mach number 0·75 Turbulent Air Jet at a Low Reynolds Number

Slot

Moore

Delfos

et al. 2009

Flow Turbulence Combust

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“…60 Taking the train centre as the base point, measuring points are arranged every 5 at a radius of 1000 m and at a height of z ¼ 3.5 m. The whole train and each bogie were selected separately as the noise source to calculate the OASPL of every measuring point for the frequency from 0 Hz to 5000 Hz. Jia et al 61 and Moore et al 62 took the radius of r ¼ 15 D and r ¼ 30 D to study the far-field noise directivity, respectively. In Figure 22(a), the directivity of the OASPL in streamwise x-y plane indicates that the directivity of the whole train has a 'figure of eight' form.…”

Section: Far-field Noise Directivitymentioning

confidence: 99%

Numerical simulation of the slipstream and aeroacoustic field around a high-speed train

Zhu

Hemida

Flynn

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part F:

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Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.

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“…The main computational bottleneck in the present model is the solution of the Poisson Eq. (14). The amount of work spent in the Poisson solver strongly depends on the type of problem and the required tolerance.…”

Section: Computational Costsmentioning

confidence: 99%

“…Unfortunately compact finite difference methods on collocated grids tend to be fairly unstable due to the low numerical dissipation. Stabilization is achieved by means of (high order) spatial filtering [19] or by the use of staggered computational grids [1,14,15]. In a previous paper by us [1] a high order compact staggered finite difference method has been developed for the compressible Navier-Stokes equations.…”

Section: Introductionmentioning

confidence: 99%

Simulation and measurement of flow generated noise

Cited by 9 publications

References 15 publications

Experiments on the Flow Field and Acoustic Properties of a Mach number 0·75 Turbulent Air Jet at a Low Reynolds Number

Experiments on the Flow Field and Acoustic Properties of a Mach number 0·75 Turbulent Air Jet at a Low Reynolds Number

Numerical simulation of the slipstream and aeroacoustic field around a high-speed train

A 6th order staggered compact finite difference method for the incompressible Navier–Stokes and scalar transport equations

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