Detached-Eddy Simulation of Landing-Gear Noise

Wang, Liang; Mockett, Charles; Knacke, Thilo; Thiele, Frank

doi:10.2514/6.2013-2069

Cited by 9 publications

(6 citation statements)

References 9 publications

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“…14 The choice of an IDDES model is motivated by the good agreement with experimental results obtained by Wang et al 15 for incompressible simulation of a landing gear flow.…”

Section: Iiia Solver Parametersmentioning

confidence: 93%

Numerical Investigation of Active Flow Control using Steady Blowing for Landing Gear Noise Reduction

Aubert

Stalnov

Angland

et al. 2014

20th AIAA/CEAS Aeroacoustics Conference

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Active Flow Control in the form of steady blowing is used with the aim of reducing the noise generated by high Reynolds number flow over bluff bodies. A Computational Fluid Dynamics solver is used to compute the flow field and provide surface pressure samples to a Ffowcs Williams-Hawkings solver to obtain far-field acoustic pressure signals. Two geometries are considered, a circular cylinder and a main strut and drag-stay configuration with the upstream drag-stay inclined by 25 • towards the upstream direction. The latter is representative of interaction flow occurring in a landing gear. The steady blowing is applied on the cylinder and drag-stay configurations from a slot located on both sides of the body at ±30 • , measured from the stagnation line. For the drag-stay configuration, blowing at 180 • is also investigated. In the isolated cylinder configuration, the noise reduction obtained by blowing at ±30 • is found to be related to a modification of the flow field directly downstream of the cylinder. An increase in the recirculation region length and a reduction of the velocity fluctuations are observed. However, applying the same flow control on the drag-stay configuration results in an increase in the overall noise. Blowing at 180 • on the drag-stay component results in a maximum reduction of 8.5 dB at the shedding peak frequency for an observer aligned with the lift dipole to the side of the drag-stay configuration. The self-noise of both components and the interaction noise are reduced. NomenclatureJet velocity ratioFrequency, Hz L Span of the main strut, m L R Dimensionless length of the recirculation region Re D Reynolds number based on the circular cylinder diameter S Spacing between two cylinders at a given spanwise location Z (center to center), m St D Strouhal number based on the main strut diameter T Total sampling time, s U Streamwise velocity, m/s y +

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“…14 The choice of an IDDES model is motivated by the good agreement with experimental results obtained by Wang et al 15 for incompressible simulation of a landing gear flow.…”

Section: Iiia Solver Parametersmentioning

confidence: 93%

Numerical Investigation of Active Flow Control using Steady Blowing for Landing Gear Noise Reduction

Aubert

Stalnov

Angland

et al. 2014

20th AIAA/CEAS Aeroacoustics Conference

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“…Mockett, Wang, Greschner, Knacke, and Eschricht. Technische Universität Berlin (TUB) have carried out compressible simulations [23] using a second-order, structured, pressure-based in-house solver. The grid consisted of around 37 M cells with boundary layers resolved to below y + = 1 on all elements.…”

Section: Tub Approachmentioning

confidence: 99%

Rudimentary Landing Gear Results at the 2012 BANC-II Airframe Noise Workshop

Spalart

Wetzel

2015

International Journal of Aeroacoustics

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The results of large-eddy and similar simulations and acoustic propagation calculations provided by six participants for the Rudimentary Landing Gear (RLG) category of the 2012 BANC-II workshop are analyzed and compared with experimental results. The general conclusion is that industrial accuracy remains elusive, and very significant differences exist between methods, so that the field needs more maturity, in addition to computing power. We present both blind comparisons from the workshop, and revised results the participants were invited to provide after having access to the experimental data. We recall that BANC-I and other comparisons indicate good code-to-code and experimental agreement for time-averaged pressures, but not so much for unsteady pressures and forces. Possibly as a result of these differences, the agreement for radiated noise is quite poor in the blind test, with typical differences of over 5 dB for the SPL and for the spectra over the dominant frequency range, and reaching 10 dB towards both ends of the spectra. The collection of numerical results brackets the experimental result. Some differences arise from misunderstandings, which were not corrected. The post-workshop results are much closer to experiment, with differences reduced to about 3 dB for SPL, and for spectra up to a Strouhal number of 15. This is not up to industrial needs, but is very encouraging and close to the accuracy achieved for jet noise. The results are sensitive to the use of solid or permeable surfaces in the Ffowcs Williams-Hawkings (FW-H) equation, and to numerous simulation details such as upwind-biased differencing.

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“…Therefore, we will choose the functions a  and a i u to be the solution of the adjoint equations defined below: (14) The equations expressed in (12), (13) and (14) construct the equations for the adjoint Green function. It includes nearly all the propagation effects from source to far field observer, namely the refraction effects caused by the flow nonuniformity and the diffraction, reflection and scattering effects caused by the solid surface.…”

Section: A Governing Equations For Acoustic Generation and Propagationmentioning

confidence: 99%

“…The current available prediction methods for airframe noise, such as the fully analytical method, the empirical and semi-empirical method and the unsteady flow based prediction method, 1 cannot entirely satisfy the engineering The airfoil trailing edge noise 4,5,6 Empirical and semi-empirical method Fast Medium Limited ANOPP 7 Physics-based prediction method 8,9,10 Unsteady-based method Very slow Medium accuracy General URANS/LES/DES+FWH 13,14 Steady-based method The paper is organized as follows: the governing equations for acoustic generation and propagation will be introduced and far field noise power spectral density by using the adjoint Green functions 22 is derived in the second section. The homogeneous and isotropic turbulence is assumed for the source modeling in second section as well.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Slat Broadband Noise with RANS Results

Bai

Guo

et al. 2015

21st AIAA/CEAS Aeroacoustics Conference

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This paper presents a RANS-based far field broadband noise prediction method for flow generated noise in low Mach number and high Reynolds number, such as slat noise. The compressible Navier-Stokes equations were linearized and reformulated firstly for acoustic generation and propagation. Then the far field noise power spectral density formulation was obtained, which relates the far field noise spectrum to the volume statistics and the exact Green's function that accounts for the sound flow coupling and propagation effects, including the diffraction and scattering effects caused by solid surfaces and the refraction effects by nonuniform flow. The adjoint Green function method was employed for the fast exact Green function computation. A semi-analytical and semi-numerical method was proposed to tackle the nearly singularity problem appeared in the computation of exact Green function. Thus, the homogeneous and isotropic turbulence was assumed for the source modeling based on the mean flow and turbulence statistics from RANS. Finally the method was applied into the prediction of slat broadband noise based on the mean flow of 30P30N multi-element airfoil at four degree of angle of attack under the uniform mean flow assumption. The computation of spatial source distribution demonstrates the downstream moving of the source location to reattachment region and the decreasing of the spatial dimension of source with the increase of the frequency. The comparison between the predicted spectral and the modeled spectral shows a good agreement in peak frequency and the middle frequency range, and demonstrate the accuracy of the method.

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Detached-Eddy Simulation of Landing-Gear Noise

Cited by 9 publications

References 9 publications

Numerical Investigation of Active Flow Control using Steady Blowing for Landing Gear Noise Reduction

Numerical Investigation of Active Flow Control using Steady Blowing for Landing Gear Noise Reduction

Rudimentary Landing Gear Results at the 2012 BANC-II Airframe Noise Workshop

Prediction of Slat Broadband Noise with RANS Results

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