Numerical Analysis of Slat Noise Generation

Knacke, Thilo; Thiele, Frank

doi:10.2514/6.2013-2162

Cited by 12 publications

(10 citation statements)

References 13 publications

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“…55 Extra computations accompanying Submission 19 (which was the sole contribution based on a reduced-order model for the slat-cove noise) provided further insights into the noise generation process by indicating two separate physical mechanisms with comparable contributions to the farfield acoustics. These two mechanisms include: a scattering of hydrodynamic fluctuations near the slat trailing edge and the acceleration of unsteady flow structures through the gap between the slat trailing edge and the main-wing leading edge.…”

Section: Open Ended Component Of Category 7 Problem Statementmentioning

confidence: 99%

Assessment of Slat Noise Predictions for 30P30N High-Lift Configuration from BANC-III Workshop

Choudhari

Lockard

2015

21st AIAA/CEAS Aeroacoustics Conference

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This paper presents a summary of the computational predictions and measurement data contributed to Category 7 of the 3 rd AIAA Workshop on Benchmark Problems for Airframe Noise Computations (BANC-III), which was held in Atlanta, GA, on June 14-15, 2014. Category 7 represents the first slat-noise configuration to be investigated under the BANC series of workshops, namely, the 30P30N two-dimensional high-lift model (with a slat contour that was slightly modified to enable unsteady pressure measurements) at an angle of attack that is relevant to approach conditions. Originally developed for a CFD challenge workshop to assess computational fluid dynamics techniques for steady high-lift predictions, the 30P30N configurations has provided a valuable opportunity for the airframe noise community to collectively assess and advance the computational and experimental techniques for slat noise. The contributed solutions are compared with each other as well as with the initial measurements that became available just prior to the BANC-III Workshop. Specific features of a number of computational solutions on the finer grids compare reasonably well with the initial measurements from FSU and JAXA facilities and/or with each other. However, no single solution (or a subset of solutions) could be identified as clearly superior to the remaining solutions. Grid sensitivity studies presented by multiple BANC-III participants demonstrated a relatively consistent trend of reduced surface pressure fluctuations, higher levels of turbulent kinetic energy in the flow, and lower levels of both narrow band peaks and the broadband component of unsteady pressure spectra in the nearfield and farfield. The lessons learned from the BANC-III contributions have been used to identify improvements to the problem statement for future Category-7 investigations. Nomenclature a = speed of sound b sim = spanwise extent of simulation domain b = model span c = chord length of stowed configuration = 0.4572 m (18 inches) c s = slat chord C d = computed overall drag coefficient (scaled by planform area c⋅b sim ) C L = computed overall lift coefficient (scaled by planform area c⋅b sim ) C L, RMS= computed RMS lift coefficient (scaled by planform area c⋅b sim ) C L,s = contribution to overall lift coefficient (scaled by planform area c⋅b sim ) from slat C L,m = contribution to overall lift coefficient (scaled by planform area c⋅b sim ) from main wing C L,f = contribution to overall lift coefficient (scaled by planform area c⋅b sim ) from flap 1 Aerospace Technologist, Computational AeroSciences Branch, M.S. 128. Associate Fellow, AIAA. 2 Aerospace Technologist, Computational AeroSciences Branch, M.S. 128. Senior Member, AIAA. 3 Team members are listed in Table 1. Downloaded by PURDUE UNIVERSITY on July 26, 2015 | http://arc.aiaa.org | 2 Cp = surface pressure coefficient = (p-p ∞ )/(ρ ∞ U ∞ 2)/2 d impingement = distance between shear layer impingement location and slat trailing edge, normalized by c K = coverage factor for confidence interval L xy = minimum distanc...

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Section: Open Ended Component Of Category 7 Problem Statementmentioning

confidence: 99%

Assessment of Slat Noise Predictions for 30P30N High-Lift Configuration from BANC-III Workshop

Choudhari

Lockard

2015

21st AIAA/CEAS Aeroacoustics Conference

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“…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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“…This interplay has also generated many ideas for reduction of slat noise, such as an inflatable filler for the slat cove, slat cusp extension, slat trailing-edge modifications, whose promise was assessed in simulations and then with laboratory tests. A recent in-depth study by Knacke et al [88] of slat noise sources on the 30P30N configuration using delayed DES is representative of the current state of the art. In addition, see Deck & Laraufie [94] for computations of a different high-lift configuration using zonal DES and comprehensive aeroacoustic analysis, including the scaling of slat and flap noise and self-excited resonances.…”

Section: (I) Slat Noisementioning

confidence: 99%

“…In addition, see Deck & Laraufie [94] for computations of a different high-lift configuration using zonal DES and comprehensive aeroacoustic analysis, including the scaling of slat and flap noise and self-excited resonances. Figure 3 reproduced from [88] shows a visualization of the turbulent flow in the slat cove region and its frequency spectrum at various stations along the mean flow streamline separating from the slat cusp. Broadband noise with a peak close to a slat chord-based Strouhal number of 2 is observed to preferentially radiate at observer angles perpendicular to the slat trailing edge.…”

Section: (I) Slat Noisementioning

confidence: 99%

“…This mechanism (referred to as an edge-dipole source [79]) is regarded as a major contributor to slat noise generation. High-fidelity simulation of the multi-element aerofoil flow, and in particular of the slat flow, using improved versions of DES (see [6,88]), implicit DES [89,90], with wallmodel LES (see [10]) and stochastic source models coupled with acoustic perturbation equation solution [91,92] has provided important insights into slat noise generation and radiation. Strong collaboration between the computations and laboratory measurements (see [93]) even when simulations were limited to two-dimensional unsteady RANS, has resulted in faster progress.…”

Section: (I) Slat Noisementioning

confidence: 99%

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A second golden age of aeroacoustics?

Lele

Nichols

2014

Phil. Trans. R. Soc. A.

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In 1992, Sir James Lighthill foresaw the dawn of a second golden age in aeroacoustics enabled by computer simulations (Hardin JC, Hussaini MY (eds) 1993 Computational aeroacoustics, New York, NY: Springer (doi:10.1007). This review traces the progress in large-scale computations to resolve the noise-source processes and the methods devised to predict the far-field radiated sound using this information. Keeping focus on aviation-related noise sources a brief account of the progress in simulations of jet noise, fan noise and airframe noise is given highlighting the key technical issues and challenges. The complex geometry of nozzle elements and airframe components as well as the high Reynolds number of target applications require careful assessment of the discretization algorithms on unstructured grids and modelling compromises. High-fidelity simulations with 200-500 million points are not uncommon today and are used to improve scientific understanding of the noise generation process in specific situations. We attempt to discern where the future might take us, especially if exascale computing becomes a reality in 10 years. A pressing question in this context concerns the role of modelling in the coming era. While the sheer scale of the data generated by large-scale simulations will require new methods for data analysis and data visualization, it is our view that suitable theoretical formulations and reduced models will be even more important in future.

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Numerical Analysis of Slat Noise Generation

Cited by 12 publications

References 13 publications

Assessment of Slat Noise Predictions for 30P30N High-Lift Configuration from BANC-III Workshop

Assessment of Slat Noise Predictions for 30P30N High-Lift Configuration from BANC-III Workshop

Prediction of Slat Broadband Noise with RANS Results

A second golden age of aeroacoustics?

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