Jeremy Webster

Framework for wind noise studies

Morgan and Raspet [J. Acoust. Soc. Am. 92, 1180–1183 (1992)] performed simultaneous wind velocity and wind noise measurements and determined that the wind noise spectrum is highly correlated with the wind velocity spectrum. In this paper, two methods are developed for predicting the upper limits of wind noise pressure spectra from fluctuating velocity spectra in the inertial range. Lower limits on wind noise are estimated from two theories of the pressure fluctuations that occur in turbulence when no wind screen or microphone is present. Empirical results for the self-noise of spherical and cylindrical windscreens in substantially nonturbulent flows are also presented. Measurements of the wind velocity spectra and wind noise spectra from a variety of windscreens are described and compared to the theoretical predictions. The wind noise data taken at the height of the anemometer lies between the upper and lower limits and the predicted self-noise is negligible. The theoretical framework allows windscreen re...

Low frequency wind noise contributions in measurement microphones

In a previous paper [R. Raspet, et al., J. Acoust. Soc. Am. 119, 834-843 (2006)], a method was introduced to predict upper and lower bounds for wind noise measured in spherical wind-screens from the measured incident velocity spectra. That paper was restricted in that the predictions were only valid within the inertial range of the incident turbulence, and the data were from a measurement not specifically designed to test the predictions. This paper extends the previous predictions into the source region of the atmospheric wind turbulence, and compares the predictions to measurements made with a large range of wind-screen sizes. Predictions for the turbulence-turbulence interaction pressure spectrum as well as the stagnation pressure fluctuation spectrum are calculated from a form fit to the velocity fluctuation spectrum. While the predictions for turbulence-turbulence interaction agree well with measurements made within large (1.0 m) wind-screens, and the stagnation pressure predictions agree well with unscreened gridded microphone measurements, the mean shear-turbulence interaction spectra do not consistently appear in measurements.

Wind noise measured at the ground surface

Measurements of the wind noise measured at the ground surface outdoors are analyzed using the mirror flow model of anisotropic turbulence by Kraichnan [J. Acoust. Soc. Am. 28(3), 378-390 (1956)]. Predictions of the resulting behavior of the turbulence spectrum with height are developed, as well as predictions of the turbulence-shear interaction pressure at the surface for different wind velocity profiles and microphone mounting geometries are developed. The theoretical results of the behavior of the velocity spectra with height are compared to measurements to demonstrate the applicability of the mirror flow model to outdoor turbulence. The use of a logarithmic wind velocity profile for analysis is tested using meteorological models for wind velocity profiles under different stability conditions. Next, calculations of the turbulence-shear interaction pressure are compared to flush microphone measurements at the surface and microphone measurements with a foam covering flush with the surface. The measurements underneath the thin layers of foam agree closely with the predictions, indicating that the turbulence-shear interaction pressure is the dominant source of wind noise at the surface. The flush microphones measurements are intermittently larger than the predictions which may indicate other contributions not accounted for by the turbulence-shear interaction pressure.

Improved prediction of the turbulence-shear contribution to wind noise pressure spectra

In previous research [Raspet et al., J. Acoust. Soc. Am. 123(3), 1260-1269 (2008)], predictions of the low frequency turbulence-turbulence and turbulence-mean shear interaction pressure spectra measured by a large wind screen were developed and compared to the spectra measured using large spherical wind screens in the flow. The predictions and measurements agreed well except at very low frequencies where the turbulence-mean shear contribution dominated the turbulence-turbulence interaction pressure. In this region the predicted turbulence-mean shear interaction pressure did not show consistent agreement with microphone measurements. The predicted levels were often much larger than the measured results. This paper applies methods developed to predict the turbulence-shear interaction pressure measured at the ground [Yu et al., J. Acoust. Soc. Am. 129(2), 622-632 (2011)] to improve the prediction of the turbulence-shear interaction pressure above the ground surface by incorporating a realistic wind velocity profile and realistic turbulence anisotropy. The revised prediction of the turbulence-shear interaction pressure spectra compares favorably with wind-screen microphone measurements in large wind screens at low frequency.

Wind noise under a pine tree canopy

It is well known that infrasonic wind noise levels are lower for arrays placed in forests and under vegetation than for those in open areas. In this research, the wind noise levels, turbulence spectra, and wind velocity profiles are measured in a pine forest. A prediction of the wind noise spectra from the measured meteorological parameters is developed based on recent research on wind noise above a flat plane. The resulting wind noise spectrum is the sum of the low frequency wind noise generated by the turbulence-shear interaction near and above the tops of the trees and higher frequency wind noise generated by the turbulence-turbulence interaction near the ground within the tree layer. The convection velocity of the low frequency wind noise corresponds to the wind speed above the trees while the measurements showed that the wind noise generated by the turbulence-turbulence interaction is near stationary and is generated by the slow moving turbulence adjacent to the ground. Comparison of the predicted wind noise spectrum with the measured wind noise spectrum shows good agreement for four measurement sets. The prediction can be applied to meteorological estimates to predict the wind noise under other pine forests.

Wind fence enclosures for infrasonic wind noise reduction.

A large porous wind fence enclosure has been built and tested to optimize wind noise reduction at infrasonic frequencies between 0.01 and 10 Hz to develop a technology that is simple and cost effective and improves upon the limitations of spatial filter arrays for detecting nuclear explosions, wind turbine infrasound, and other sources of infrasound. Wind noise is reduced by minimizing the sum of the wind noise generated by the turbulence and velocity gradients inside the fence and by the area-averaging the decorrelated pressure fluctuations generated at the surface of the fence. The effects of varying the enclosure porosity, top condition, bottom gap, height, and diameter and adding a secondary windscreen were investigated. The wind fence enclosure achieved best reductions when the surface porosity was between 40% and 55% and was supplemented by a secondary windscreen. The most effective wind fence enclosure tested in this study achieved wind noise reductions of 20-27 dB over the 2-4 Hz frequency band, a minimum of 5 dB noise reduction for frequencies from 0.1 to 20 Hz, constant 3-6 dB noise reduction for frequencies with turbulence wavelengths larger than the fence, and sufficient wind noise reduction at high wind speeds (3-6 m/s) to detect microbaroms.

Infrasonic wind noise under a deciduous tree canopy

In a recent paper, the infrasonic wind noise measured at the floor of a pine forest was predicted from the measured wind velocity spectrum and profile within and above the trees [Raspet and Webster, J. Acoust. Soc. Am. 137, 651-659 (2015)]. This research studies the measured and predicted wind noise under a deciduous forest with and without leaves. A calculation of the turbulence-shear interaction pressures above the canopy predicts the low frequency peak in the wind noise spectrum. The calculated turbulence-turbulence interaction pressure due to the turbulence field near the ground predicts the measured wind noise spectrum in the higher frequency region. The low frequency peak displays little dependence on whether the trees have leaves or not. The high frequency contribution with leaves is approximately an order of magnitude smaller than the contribution without leaves. Wind noise levels with leaves are very similar to the wind noise levels in the pine forest. The calculated turbulence-shear contribution from the wind within the canopy is shown to be negligible in comparison to the turbulence-turbulence contribution in both cases. In addition, the effect of taller forests and smaller roughness lengths than those of the test forest on the turbulence-shear interaction is simulated based on measured meteorological parameters.

Mechanisms for wind noise reduction by a spherical wind screen

Spherical wind screens provide wind noise reduction at frequencies which correspond to turbulence scales much larger than the wind screen. A popular theory is that reduction corresponds to averaging the steady flow pressure distribution over the surface. Since the steady flow pressure distribution is positive on the front of the sphere and negative on the back of the sphere, the averaging results in a reduction in measured wind noise in comparison to an unscreened microphone. A specially constructed 180 mm diameter foam sphere allows the placement of an array of probe microphone tubes just under the surface of the foam sphere. The longitudinal and transverse correlation lengths as a function of frequency and the rms pressure fluctuation distribution over the sphere surface can be determined from these measurements. The measurements show that the wind noise correlation lengths are much shorter than the correlations measured in the free stream. The correlation length weighted pressure squared average over the surface is a good predictor of the wind noise measured at the center of the wind screen. [This work was supported by the Army Research Laboratory under Cooperative Agreement W911NF-13-2-0021.]

Experimental investigation of large porous wind fences for infrasonic wind noise reduction

An extensive experimental investigation of large porous wind fences constructed from commercially available materials has recently been completed. Measured changes to the wind noise, turbulence, and wind velocity profile inside the fence resulting from varying the fence’s height, diameter, and porosity have been measured. The effect of other variables, including porous roofs, a bottom gap, and the addition of secondary windscreens were also studied. An empirical model based on measurements of the turbulence correlation length around the outside of the fence and the velocity gradient across the fences surface has been derived to develop a better understanding of the wind noise reduction mechanisms. The measurements and model are then used to suggest an optimized wind fence design and predict the band width and magnitude of the wind noise reduction curve.

Low‐frequency wind noise reduction by spherical windscreens

Spherical windscreens are surprisingly effective at reducing wind noise at frequencies for which the turbulence scale is much larger than the windscreen. In the 1930s, Phelps postulated that the low‐frequency reduction of windscreens could be explained by assuming that the dc flow pressure distribution around a sphere also applied to low‐frequency fluctuations and wind noise. The area average of the dc pressure distribution was then calculated and shown to be smaller than the stagnation pressure. Morgan extended this idea by measuring the pressure distribution around a porous foam windscreen. Recent measurements [Webster et al., J. Acoust. Soc. Am. 118, 2009 (2005)] have shown that the pressure fluctuations at low frequency do not follow the dc distribution and that the velocity and pressure fluctuation correlations are drastically reduced by the presence of the windscreen. A simple calculation demonstrates that the decorrelation of the pressure fluctuations is sufficient to explain the observed low‐frequ...