Generic Airfoil Trailing-Edge Noise Prediction using Stochastic Sound Sources from Synthetic Turbulence

Rautmann, Christof; Dierke, Jürgen; Ewert, Roland; Hu, Naifei; Delfs, Jan

doi:10.2514/6.2014-3298

Cited by 17 publications

(25 citation statements)

References 15 publications

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“…In a first step the turbulent flow around the airfoil is derived from steady RANS simulation d . For BANC-III the two-equation Menter-SST turbulence model 32 is used, for details refer to Rautmann et al 38 A CAA simulation is carried out in the second step solving Acoustic Perturbation Equations (APE 14 ) on a structured multi-block (SMB) mesh. RANS flow provides the mean-flow for the time-dependent aeroacoustic simulation and the turbulence statistics to synthesize stochastic vortex sound sources that drive the governing equations.…”

Section: Iiia2 Dlr Approach: Caa Code Piano With Rans-based Stochamentioning

confidence: 99%

Broadband Trailing-Edge Noise Predictions—Overview of BANC-III Results

Herr

Ewert

Rautmann

et al. 2015

21st AIAA/CEAS Aeroacoustics Conference

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in Atlanta, Georgia, USA. The objective of this workshop was to assess the present computational capability in the area of physics-based prediction of different types of airframe noise problems and to advance the state-of-the-art via a combined effort. This documentation summarizes the results from workshop category 1 (BANC-III-1) which focuses on the prediction of broadband turbulent boundary-layer trailing-edge noise and related source quantities. Since the forerunner BANC-II workshop identified some room for improvements in the achieved prediction quality, BANC-III-1 relies on the same test cases, namely 2D NACA 0012 and DU96-W-180 airfoil sections in a uniform flow.Compared to BANC-II particularly the scatter among predictions for the DU96-W-180 test case could be significantly reduced. However, proposed adaptations of previously applied computational methods did not systematically improve the prediction quality for all requested parameters. The category 1 workshop problem remains a challenging simulation task due to its high requirements on resolving and modeling of turbulent boundary-layer source quantities.Downloaded by PURDUE UNIVERSITY on July 26, 2015 | http://arc.aiaa.org |

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Section: Iiia2 Dlr Approach: Caa Code Piano With Rans-based Stochamentioning

confidence: 99%

Broadband Trailing-Edge Noise Predictions—Overview of BANC-III Results

Herr

Ewert

Rautmann

et al. 2015

21st AIAA/CEAS Aeroacoustics Conference

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“…Therefore, further simulations are carried out concentrating on interaction noise of turbulence with the Similar noise sources that are based on turbulence-geometry interaction, such as airfoil trailing-edge noise or high-lift slat noise have already been successfully approached with different source formulations. 8,9,[15][16][17] Therewith, the fluctuating vorticity is implemented a a deterministic source term on the right-hand side of the Acoustiuc Perturbation Equations (APE). 18 However, this method is not directly applicable to the acoustic simulations of the circulation-controlled airfoil.…”

Section: Iib2 Turbulence-geometry Interaction Noisementioning

confidence: 99%

Numerical and experimental insights into the noise generation of a circulation control airfoil

Rossian

Suryadi

Rossignol

et al. 2018

2018 AIAA/CEAS Aeroacoustics Conference

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With the advances in reduction of propulsion related noise from aircraft, airframe noise gets more and more into focus. During approach and landing, the high-lift system of the wings becomes one major acoustic source region contributing to the overall emitted noise. One promising approach to reduce this airframe noise is to change the complete high-lift system from a classic three element slat-wing-flap configuration to a slot-less system with active blowing and droop nose. Preceding experimental investigations have shown, that such a configuration may provide a noise reduction above 2 kHz on the model scale. In the present paper both numerical and experimental investigations concerning the acoustics of a high-lift wing with droop nose and active blowing are presented. Thereby, an insight into the acoustic source mechanisms for different aerodynamic setups is provided that in the future will serve as a basis for the design of a low-noise high-lift configuration. It was found, that in principle three source mechanisms are to be considered. In the low to mid frequency domain, mostly turbulence-geometry interaction noise such as trailing edge noise, jet-nozzle interaction noise and curvature noise from the flow being bent around the flap are supposed to be the driving mechanisms. Moreover, the high frequency domain is found to be dominated by mixing noise from the high speed jet. NomenclatureA = wing area [m 2 ] b = wing span [m] c = chord length [m] c µ = jet momentum coefficient h = height [m] m = mass flow kg s M a = Mach number p = pressure [Pa] Re = Reynolds number R s = specific gas constant J kg K T = temperature [K] U = scalar velocity magnitude m s

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“…The turbulence spectra generated with FRPM are Gaussian, refer to the discussion in Appendix A.1. The generation of generalized turbulence spectra has been discussed in recent work by Rautmann et al 25 and Wohlbrandt et al 24 Details of the approach as far as they concern the present discussion are presented in Appendix A.3. Effectively, standard turbulence spectra are generated through the weighted summation of M independent FRPM realizations of Gaussian spectra with successively increased length scale.…”

Section: Effect Of Diffusion Addedmentioning

confidence: 99%

Canonical Stochastic Realization of Turbulent Sound Sources via Forced Linear Advection-Diffusion-Dissipation Equation

Ewert

2016

22nd AIAA/CEAS Aeroacoustics Conference

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Stochastic sound sources derived from Reynolds Averaged Navier-Stokes (RANS) solution are recognized in Computational Aeroacoustics as one possible way to efficiently predict broadband sound. In this paper a stochastically forced linear advection-diffusiondissipation equation is introduced. The model provides spectra and anisotropic two-point correlations that otherwise have to be incorporated in datum stochastic methods as additional model assumptions. The output are fluctuating velocity components, from which vortex sound sources derive. The forcing is white (delta-correlated) in time and possess a finite correlation length scale in space. The well-posedness is demonstrated in the paper. A solenoidal forcing term is shown to realize the correlation tensor of homogeneous isotropic turbulence together with a longitudinal turbulence spectrum that exhibits a plateau for lower frequencies followed by a characteristic power law roll-off and final cutoff. Exponent of decay and cutoff are adjustable. The stochastic partial differential equation involves a diffusion parameter, a timescale , a redistribution tensor, and a forcing variance. Transport equations for Reynolds stresses and turbulence kinetic energy derive from it that have the canonical form of major RANS transport equations. In particular, all parameters needed can be assigned to corresponding RANS parameters so that an accurate reproduction of RANS one-point statistics becomes feasible. For the generation of two-point statistics the hypothesis from turbulence modeling is adopted that the present model calibrated for homogeneous isotropic turbulence is also applicable for more general flows.

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Generic Airfoil Trailing-Edge Noise Prediction using Stochastic Sound Sources from Synthetic Turbulence

Cited by 17 publications

References 15 publications

Broadband Trailing-Edge Noise Predictions—Overview of BANC-III Results

Broadband Trailing-Edge Noise Predictions—Overview of BANC-III Results

Numerical and experimental insights into the noise generation of a circulation control airfoil

Canonical Stochastic Realization of Turbulent Sound Sources via Forced Linear Advection-Diffusion-Dissipation Equation

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