Semi-Empirical Modeling of Turbulent Anisotropy for Airfoil Self Noise Prediction

Kamruzzaman, Mohammad; Lutz, Th.; Herrig, Andreas; Krämer, Ewald

doi:10.2514/6.2010-3878

Cited by 11 publications

(28 citation statements)

References 6 publications

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“…Finally, predictions for and Λ by DLR, IAG and DTU are compared to equivalently post-processed measurement data. 27,29,30 Corresponding predictions are not included in the PoliTo results because the applied SA-QCR turbulence model does not provide these values. For the profiles similar observations can be made as during BANC-II-1; when approaching the wall, is generally overpredicted by DLR and DTU (the latter providing overall larger values than the two other approaches), whereas the IAG method contains a dedicated near-wall correction.…”

Section: Ivb Comparison Of Near Wake Flow Characteristicsmentioning

confidence: 98%

“…6,27,29,35 Rnoise incorporates a derivative of the frequently applied prediction schemes based on Blake's 6 approach, herein referred to as 'Blake-TNO' models because the most widespread (mainly in the context of low-noise wind turbine profile design efforts) is the variant published by Parchen, 35 TNO. The general Blake-TNO approach reads…”

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

confidence: 99%

“…Moreover, the underlying well-documented measurement chains and model hardware have been recently used 23,40 and are still available for follow-on tests (for BANC-IV, etc.). a The test cases #1 to #4 have been mainly defined based on the availability of measured turbulence length scales and measured transition locations for these conditions, 23,29,30 while corresponding TEN and surface pressure data have been made available by scaling of multiple available data sets according to the problem statement. Case #5 for which no detailed flow survey is available corresponds to the original acoustic measurement conditions.…”

Section: Problem Statementmentioning

confidence: 99%

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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: Ivb Comparison Of Near Wake Flow Characteristicsmentioning

confidence: 98%

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

confidence: 99%

Section: Problem Statementmentioning

confidence: 99%

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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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“…(14), or semi-empirical model of Ref. 25. The first two methods from the above discussed models have been used in XEnoise to compute the integral length scale.…”

Section: Anisotropic ⌳ 2 Based On An Anisotropic Factor F 22 Anisomentioning

confidence: 99%

“…Besides the above discussed isotropic length scales, a model for the calculation of anisotropic vertical integral length scale has also been implemented in the Rnoise method 22,25 . The final form of the modeled anisotropic length scale equation is…”

Section: Anisotropic ⌳ 2 Based On An Anisotropic Factor F 22 Anisomentioning

confidence: 99%

Comprehensive evaluation and assessment of trailing edge noise prediction based on dedicated measurements

Kamruzzaman¹,

Herrig²,

Krämer³

et al. 2011

Noise Control Eng. J.

Self Cite

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An extensive assessment and step by step validation of turbulent boundary-layer trailing-edge interaction (TBL-TE) noise prediction was conducted based on the boundary layer properties calculated by three different aerodynamics methods, XFOIL, Wilcox EDDYBL and the RANS solver FLOWer. For this purpose detailed measurements of turbulent boundary-layer properties like two-point turbulent velocity correlations, the spectrum of the associated wall pressure fluctuations (WPFs) and the emitted trailing-edge noise have been performed in the Laminar Wind Tunnel (LWT). The measurements were performed for the NACA 0012 airfoil. Most of the investigated cases show that the numerical WPF and far-field radiated noise models capture the measured peak amplitude level as well as the peak position remarkably well, if the turbulence noise source parameters are estimated properly including turbulence anisotropy effects. © 2011 Institute of Noise Control Engineering.

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Trailing edge noise reduction of wind turbine blades by active flow control

et al. 2014

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In the current study, we investigate a route to reduction of the turbulent boundary layer–trailing edge interaction noise. The trailing edge noise is generated by surface pressure fluctuations beneath a turbulent boundary and scattered at the trailing edge of wind turbine blades. Trailing edge noise is considered to be the dominant noise source of modern wind turbines. Therefore, efforts are constantly made to attenuate the noise. Today, noise emission can be reduced by proper airfoil design or passive devices, such as trailing edge serrations. A further improved candidate technology for trailing edge noise attenuation is active flow control in the form of wall‐normal suction. With active flow control, the boundary layer features responsible for trailing edge noise generation can be manipulated, and correspondingly the trailing edge noise can be reduced. Detailed experimental investigations were performed at the Universities of Tel‐Aviv and Stuttgart. The tests showed that steady wall‐normal suction has a positive effect on the trailing edge noise by reducing the boundary layer thickness, and with it the integral length scales of the eddies within the boundary layer. Copyright © 2014 John Wiley & Sons, Ltd.

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Semi-Empirical Modeling of Turbulent Anisotropy for Airfoil Self Noise Prediction

Cited by 11 publications

References 6 publications

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

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

Comprehensive evaluation and assessment of trailing edge noise prediction based on dedicated measurements

Trailing edge noise reduction of wind turbine blades by active flow control

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