LES prediction of wall‐pressure fluctuations and noise of a low‐speed airfoil

2008 ◽  
Vol 123 (5) ◽  
pp. 3538-3538 ◽  
Author(s):  
Meng Wang ◽  
Stéphane Moreau ◽  
Gianluca Iaccarino ◽  
Michel Roger
Keyword(s):  
Pressure Fluctuations ◽  
Wall Pressure ◽  
Low Speed ◽  
Wall Pressure Fluctuations

LES Prediction of Wall-Pressure Fluctuations and Noise of a Low-Speed Airfoil

2009 ◽  
Vol 8 (3) ◽  
pp. 177-197 ◽  
Author(s):  
Meng Wang ◽  
Stephane Moreau ◽  
Gianluca Iaccarino ◽  
Michel Roger
Keyword(s):  
Boundary Layer ◽  
Wind Tunnel ◽  
Pressure Fluctuations ◽  
Wall Pressure ◽  
Transition To Turbulence ◽  
Trailing Edge ◽  
Frequency Spectra ◽  
Potential Core ◽  
Low Speed ◽  
Wall Pressure Fluctuations

This paper discusses the prediction of wall-pressure fluctuations and noise of a low-speed flow past a thin cambered airfoil using large-eddy simulation (LES). The results are compared with experimental measurements made in an open-jet anechoic wind-tunnel at Ecole Centrale de Lyon. To account for the effect of the jet on airfoil loading, a Reynolds-averaged Navier-Stokes calculation is first conducted in the full wind-tunnel configuration, and the mean velocities from this calculation are used to define the boundary conditions for the LES in a smaller domain within the potential core of the jet. The LES flow field is characterized by an attached laminar boundary layer on the pressure side of the airfoil and a transitional and turbulent boundary layer on the suction side, in agreement with experimental observations. An analysis of the unsteady surface pressure field shows reasonable agreement with the experiment in terms of frequency spectra and spanwise coherence in the trailing-edge region. In the nose region, characterized by unsteady separation and transition to turbulence, the wall-pressure fluctuations are highly sensitive to small perturbations and thus diffcult to predict or measure with certainty. The LES, in combination with the Ffowcs Williams and Hall solution to the Lighthill equation, also predicts well the radiated trailing-edge noise. A finite-chord correction is derived and applied to the noise prediction, which is shown to improve the overall agreement with the experimental sound spectrum.

The Quantification of Internal Noise Levels and Wall Pressure Spectra in Industrial Gas Pipelines

1991 ◽  
Author(s):  
M. P. Norton ◽  
A. Pruiti
Keyword(s):  
Prediction Models ◽  
Transmission Loss ◽  
Pressure Fluctuations ◽  
Internal Noise ◽  
Wall Pressure ◽  
Gas Pipelines ◽  
Noise Levels ◽  
Empirical Prediction ◽  
Wall Pressure Fluctuations ◽  
Semi Empirical

Abstract This paper addresses the issue of quantifying the internal noise levels/wall pressure fluctuations in industrial gas pipelines. This quantification of internal noise levels/wall pressure fluctuations allows for external noise radiation from pipelines to be specified in absolute levels via appropriate noise prediction models. Semi-empirical prediction models based upon (i) estimated vibration levels and radiation ratios, (ii) semi-empirical transmission loss models, and (iii) statistical energy analysis models have already been reported on by Norton and Pruiti 1,3 and are not reported on here.

Prediction of Elbow Flow Dynamics Using Correlated Wall Pressure Data

2018 ◽  
Author(s):  
André Baramili ◽  
Ludovic Chatellier ◽  
Laurent David ◽  
Loïc Ancian
Keyword(s):  
Pressure Fluctuations ◽  
Wall Pressure ◽  
Partial Least Square ◽  
Flow Dynamics ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Multiple Time ◽  
Duct Flow ◽  
Flow Induced Vibration ◽  
Wall Pressure Fluctuations

The present study focuses on the analysis of the flow-induced vibration phenomenon typically encountered on piping systems containing an elbow. The correlation between the turbulent flow through the elbow and the dynamic forcing it yields on the piping walls was assessed experimentally. A closed water loop containing a transparent elbow was designed in order to develop fully turbulent duct flow condition. Particle Image Velocimetry (PIV) was applied in the transparent zone in order to provide unsteady data on the flow dynamics through the elbow; simultaneously, wall pressure fluctuations were measured on and around the elbow. Several flow configurations were tested in order to obtain a large coupled database linking the flow features to the resulting dynamic excitation on the walls. Finally, Partial Least Square Regression (PLSR) was applied in order to harvest the correlated information contained in multiple pressure signals at multiple time-delays and build a relationship capable of estimating the temporal evolution of the velocity field using a set of measured wall pressure signals.

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