Jiao Yu

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.

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...

The pressure distribution around foam spheres outdoors

A previous investigation of the pressure fluctuations around foam windscreens outdoors indicated both lower pressure levels and lower correlations between microphones than expected from wind noise theory [J. Acoust. Soc. Am. 116, 2517]. The measurement set was limited and suffered from uncertainty in the incoming wind direction. In this paper we show results from several new measurements which use a three‐axis sonic anemometer to establish the wind direction and speed simultaneous to pressure correlation measurements. [Prepared in part through collaborative participation in the Collaborative Technology Alliance for Advanced Sensors sponsored by the U.S. Army Research Laboratory.]

Measurement of wind noise levels in streamlined probes

This paper investigates the wind noise pressure spectra measured by aerodynamically designed devices in turbulent flow. Such measurement probes are often used in acoustic measurements in wind tunnels to reduce the pressure fluctuations generated by the interaction of the devices with the incident flow. When placed in an outdoor turbulent environment however, their performance declines noticeably. It is hypothesized that these devices are measuring the stagnation pressures generated by the cross flow components of the turbulence. Predictions for the cross flow contribution to the stagnation pressure spectra based on measured velocity spectra are developed, and are then compared to the measured pressure spectra in four different probe type devices in windy conditions outdoors. The predictions agree well with the measurements and show that the cross flow contamination coefficient is on the order of 0.5 in outdoor turbulent flows in contrast to the published value of 0.15 for measurements in a turbulent jet indoors.

New Systems for Wind Noise Reduction for Infrasonic Measurements

Wind noise is a significant problem for infrasound detection and localization systems. Pipe arrays are commonly used for suppressing wind noise by area averaging the relatively incoherent wind noise. The area averaging and physical construction of the pipe arrays limit the ability of the array to measure infrasound pulses with waveform fidelity. The need for waveform fidelity is motivated by the recent increase in the ability to predict waveforms theoretically from the meteorology data. This chapter investigates large cylindrical and hemispherical porous windscreens, which employ single-point sensors with little or no waveform distortion. The theory of wind noise generation is briefly outlined to provide a basis for understanding the windscreen research. Next, four recent experiments measuring the wind noise reduction of porous cylindrical screens with respect to bare sensors mounted flush with the ground, the wind noise reduction of porous fabric domes with respect to a sensor sitting on the ground surface, the wind noise reduction of porous metal domes with respect to other sensors, and the wind noise reduction of porous cylinders and fabric domes with respect to flush-mounted sensors and each other. The second and third experiments also demonstrate the ability of the windscreens to record impulses with waveform fidelity. The largest screens provide up to 20 dB of wind noise reduction down to wavenumbers on the order of the inverse of the height of the windscreen. A theory of wind noise reduction is developed and leads to a better understanding of the relative contribution of wind noise generated at the surface of the screen and wind noise generated by flow through the screen. It is concluded that construction of domes large enough to provide signal enhancement down to 0.1 Hz is feasible and would provide high fidelity time waveforms for comparison with theoretical predictions.

Comparison of surface wind noise predictions from mirror flow and rapid-distortion models of atmospheric turbulence

For atmospheric acoustic measurements at the ground surface, the principal source of the intrinsic wind noise is shearing of the turbulence by the mean flow. The pressure spectra from this turbulence-shear mechanism depend on two-point statistics of the anisotropic, inhomogeneous atmospheric turbulence. The inhomogeneity of the surface-normal velocity component can be realistically modeled by the mirror flow, which is a superposition of two correlated isotropic turbulent fields in transformed coordinates. Another analytical framework is rapid-distortion theory, which approximates the turbulence as the result of linearized distortion of an initially homogeneous field by the mean flow. This study compares turbulence-shear spectra calculated with the mirror flow model and rapid-distortion models for both surface blocking effects and mean shear distortion. For each case, the model parameters are estimated by fits to the single-point velocity spectra recorded in a recent experiment near Laramie, Wyoming. The s...

New calculation of the turbulence-turbulence contribution to wind noise pressure spectra by incorporating turbulence anisotropy

Turbulence-turbulence interaction and turbulence-shear interaction are the sources of intrinsic pressure fluctuation for wind noise generated by atmospheric turbulence. In previous research [Yu et al., J. Acoust. Soc. Am. 129(2), 622–632 (2011)], it was shown that the measured turbulent fields outdoors can be realistically modeled with Kraichnan’s mirror flow model and turbulence-shear interaction pressure spectra at the surface were predicted and compared to measurements. This paper continues to apply Kraichnan’s model and calculates the turbulence-turbulence interaction wind noise pressure spectra under anisotropic turbulence conditions. Different from turbulence-shear interaction, the fourth-order moments of the turbulence are needed in the calculation. A new calculation of the turbulence-turbulence contribution to the wind noise pressure spectra is compared to that for isotropic turbulence and the results are analyzed. [Work supported by the U. S. Army Research Office (Grant No. W911NF-12-0547) and th...

Investigation of dominant sources of infrasonic wind noise in ground level microphones.

A two part project has investigated whether the pressure fluctuations (infrasonic wind noise) at the ground, as measured in an open field, can be predicted from the vertical wind velocity measured above the ground. The dominant region contributing to the pressure on the ground is calculated theoretically and displayed with contour plots. Experimentally, time dependent correlations between the measured pressure and wind velocities were done. The correlation coefficients were very low, typically between 0.08–0.15, for broadband frequencies up to 5 Hz. Cross spectrum analysis and application of octave band pass filters showed the dominant frequencies for correlations to be around 0.07–0.1 Hz, with correlation coefficients typically between 0.3–0.5. [Project funded by the US Army Space and Missile Defense Command.]