An experimental characterisation of wall pressure wavevector-frequency spectra in the presence of pressure gradients

Abstract

The goal of this experimental study is to investigate the wall pressure wavenumberfrequency spectra induced by a turbulent boundary layer in the presence of a mean pressure gradient. The mean pressure gradient is achieved by changing the ceiling angle of a rectangular channel flow. Wall pressure spectra are measured for zero-, adverse-and favorablepressure-gradient boundary layers by using a pinhole microphone in conjunction with a high-frequency-calibration procedure. A linear antenna based on a non-uniform distribution of remote microphones mounted on a rotating disk is also developed to obtain a direct measurement of both aerodynamic and acoustic components of wavenumber-frequency spectra. First results, comparisons and analyses are then discussed. Nomenclature C ppressure coefficient h height of the channel H = δ 1 /δ θ shape factor k wavevector (k ∈ I R 3 ) p w wall pressure q 0 = ρU 2 0 /2 dynamic pressure Re δ 1 = U ∞ δ 1 /ν Reynolds number based on δ 1 Re + = u τ δ/ν Kármán or friction Reynolds number r separation vector (polar coordinates) R pp (r, ω) pressure cross spectral density S pp (ω) = R pp (r = 0, ω) one-sided wall pressure spectrum

Aeroacoustics of an axial ducted low Mach-number stage: numerical and experimental investigation

“…4,6 Every single sensor has been calibrated in frequency (amplitude and phase) using a calibration tube and a reference sensor. 7 Moreover, a global calibration method developed by Leclère et al 8 has also been applied with success. The calibration results are presented in the section IV.A.…”

“…The individual method must be performed for each microphone using a calibration device described in. 7,8 A loudspeaker (driver unit) is used to generate a broadband signal (white noise) covering the frequency band of interest. The source is deported using a hose at the end of which the calibration device is located.…”

CFD Modeling of a Realistic Turbofan Blade for Noise Prediction. Part 2: Analytical Acoustic Predictions

“…The spanwise coherence length l y is modeled using the Salze-Efimtsov model which is an adaptation of the empirical model obtained by Efimtsov (Efimtsov, 1982) to overcome the unphysical behavior of Corcos's model at low frequency (Salze et al, 2014).…”

The Design, Fabrication, and Commissioning of a High-Speed Aeroacoustic Wind Tunnel for Studies of Surface Pressure Fluctuations Beneath Turbulent Boundary Layers

“…It is universally accepted that viscous effects dominate in this region and thus the spectrum best collapses when scaled based on kinematic viscosity, ν, and other inner layer variables (wall shear stress, τ w ; and friction velocity, u τ ) [7]. Early measurements conducted by Schewe [31] within this frequency region indicated a dependence of the spectrum on ω −7/3 , however more recent measurements with smaller transducer sizes have shown an attenuation slope ranging from ω −5 to ω −7 for very high frequencies [8,17,22,23,26,28,30]. The transition from the ω −7/3 minor decay region to the larger decay region seems to relate to the transition from the buffer layer to the viscous sub-layer within the TBL [17].…”

“…Typically this region is normalized by parameters which influence both the inner and outer regions of the boundary layer (TBL thickness, δ; friction velocity, u τ ; and wall shear stress, τ w ) [7]. The mid-frequency region contains an energy peak, which has been found to occur around ωδ/u τ = 50 [23,27,28]. Theoretically, it is generally accepted that the spectrum should start to attenuate according to an approximate ω −1 power law after the spectral peak [7,25,27,29].…”