Agenda

The results of physical modeling of the scattering of infrasound signals generated by pulsed sources (surface explosions, volcanoes) from layered wind velocity and temperature inhomogeneities in the stratosphere and lower thermosphere by studying the scattering of acoustic pulses generated by an artificial detonation generator from a thin layered structure of a stably-stratified atmospheric boundary layer (ABL) are presented. Based on the forms and travel times of scattered signals in the acoustic shadow region, the instantaneous vertical profiles of wind velocity fluctuations in the thin layers of the ABL located at different heights (up to 700 m) above the ground and at different distances from the source (up to 2.75 km) were reconstructed. A similarity is shown between the propagation of infrasound signals from surface explosions (20-70 t of TNT) in a “shallow” tropospheric waveguide and the propagation of the Lamb mode from nuclear explosions. The long-range propagation of infrasound signals from ground-based explosions in stratospheric waveguides was also simulated by studying the waveguide propagation of acoustic pulses in the ABL in the morning hours (after sunrise), when convection under an elevated layer of temperature inversion forms a vertical profile of the effective sound speed similar to that in a stratospheric waveguide. This work was supported by the RFBR N 18-55-05002.

Over the past decade, plans to develop a new generation of supersonic passenger aircrafts have spurred interest in the problem of sonic boom propagation in the atmosphere. New designs are focused on reducing loudness of resulting sonic boom signature on the ground in order to fit regulators constraints. This task is related to aerodynamical optimizations and signature propagation through homogeneous atmosphere. Important wave propagation effects occur in a few kilometers above the ground where sonic boom is affected by turbulence of the planetary boundary layer. Theoretical analysis of the effects of turbulence is usually based on one-way model equations of different complexity. Most frequently used equation is the nonlinear parabolic equation of Khokhlov-Zabolotskaya-Kuznetsov-type. Paraxial approximation of diffraction effects inherent to this equation limits diffraction and scattering angles. The diffraction term can be improved by using wide-angle formulation of different forms. In this work simulation results for N-wave propagation through homogeneous isotropic turbulence are compared for standard and wide-angle parabolic equations. The wide-angle model is based on 45 degrees Claerbout approximation of the propagation operator. Differences between the acoustic field and statistics of N-wave parameters obtained in narrow- and wide-angle propagation models are discussed [Work supported by RSF-18-72-00196 and ANR-10-LABX-0060/ANR-16-IDEX-0005].

In the context of a research on the measurement of long-range attenuation of noise from terrestrial sound sources, a parametric study of atmospheric sound propagation channel characteristics as a function of source height, ground characteristics and meteorological conditions is presented in this paper. The study relies on ray tracing. The Bellhop ray tracing model which is well known in underwater acoustics has been used here. In this paper, the accuracy of Bellhop’s predictions in the atmosphere is first addressed by comparison with results from Salomon’s ray model and published benchmarks cases by Attenborough et al. No significant discrepancy was noticed with respect to these references. The second part of the paper presents a parametric study for source heights ranging from 0.05 m to 200 m, a grid of receivers at ranges between 200 m and 2 km from the source and between 2 and 50 m height. A homogeneous flat absorbing ground described by a complex reflection factor is assumed. For the atmospheric conditions, a subset of the WiSi classification was considered. The results are analyzed from the point of view of the receiver and discussed in terms of attenuation, number of arrivals and number of reflections.

Bayesian inference approach to source localization typically involves computing marginals of the posterior probability density for source parameters. This is typically carried out with Markov-chain Monte Carlo methods, with various approaches applied to improve efficiency. In these methodologies, propagation models are constructed by numerically propagating signals through a set of plausible atmospheric specifications so as to obtain distributions for arrival characteristics. Such an approach, however, drastically increases the number of model runs and for this reason, long-range monitoring of geophysical events is often based on simplified stochastic propagation models. In this work, we combine the Bayesian framework and non-intrusive generalized Polynomial Chaos (gPC) to update the posterior probability density function describing the source localization. The main difference with the standard Monte Carlo method lies in the fact that the sampling is carried out over the gPC metamodel, which is built from an experimental design of limited size. This makes such propagation models more efficient than their stochastic counterparts and better suited for real-time monitoring. The performance of the method is demonstrated through reanalysis of the meteor explosion over the Bering sea, on December 18, 2018, using as many metamodels as there are IMS stations that have presumably recorded the bolide.

Investigation of infrasound emissions from tornadic storms has seen renewed interest in recent years especially as the commercial availability of infrasound sensors has increased and the desire to improve tornado warning performance (reduced false alarm and increased detection rates). Recent investigations repeatedly have indicated emissions in the 1-10 Hz band are common and can be detected more than 100 km distant even with EF-0 level storms. This presentation will compare and contrast the performance of several array data processing techniques for this application with an emphasis on techniques capable of resolving multiple sources. The impact of propagation conditions and wind noise on detection ranges will be highlighted.

This work presents the measurement of atmospheric acoustic transmission loss in a near-shore environment. This work is part of a larger project that aims to model transmission loss in long-range (~3 km) atmospheric acoustic propagation in littoral or riverine environments. The goal of the presented experiment is the evaluation of the excess attenuation introduced by a sandy shore. The site is a small pond with a sandy beach area. The acoustic source is placed at the edge of the pond whereas three 7-microphone arrays record controlled sound at the water-sand boundary (at 111 m range), at 131 m and 168 m. The collected acoustic data are used to validate a numerical model (presented in a companion work). The sand of the beach area has been characterized by measuring the grain size distribution and moisture content at regular intervals along the path. This data, together with surface impedance measurements of select samples were used to model the beach in the numerical solver. Acoustic transmission loss predicted by a numerical model is compared with data to determine how the amount of information about the shore affects the accuracy of the acoustic transmission loss prediction.

As part of the Acoustic Surveillance for Hazardous Eruptions (ASHE) project, two four-element infrasound arrays were installed in northern and central Ecuador in the Andes. The RIOE and LITE arrays were active between 2006 and 2013 recording thousands of coherent infrasound signals originating from eruptions of Tungurahua, El Reventador, and Sangay volcanoes. We use Progressive Multi-Channel Correlation array processing to identify coherent infrasound signals and determine their direction of arrival. Detections correspond to quasi-continuous activity of Sangay between early 2007 and mid 2012, at least eleven periods of acoustic activity of Tungurahua between 2006 and mid 2012, and very strong infrasound arrivals from El Reventador at both arrays in early 2008. We validate most of the infrasound detections using remote sensing results from the MODIS (Moderate Resolution Imaging Spectroradiometer) volcano detection algorithm (MODVOLC). However, MODVOLC detections may underestimate eruptive activity as volcanoes in Ecuador are often covered by clouds and the corresponding satellite data have a temporal resolution of ~1–2 days. Finally, we highlight the benefits of infrasound arrays for acoustically monitoring active volcanoes in Ecuador at distances between 37 and 250 km and describe the processes that limit volcanic infrasound signal detection at these distances.

This work presents the modeling of excess attenuation of a sandy shore and its contribution to the atmospheric sound transmission loss in a near-shore environment. This work is part of a larger project developing a numerical model of long-range (~3 km) atmospheric acoustic propagation in littoral or riverine environments with a near-shore acoustic source and on-shore receivers. The numerical model uses a parabolic equation method to account for wind and temperature variation with elevation along the propagation path. The surface impedance of a sandy shore is modelled as an equivalent fluid that takes into account the grain size distribution of the sand and its change in water content along the propagation path. The propagation range consists of three segments: over flat water, over wet sand, and over dry sand. Surface impedance estimates for the sandy shore are made based on measured grain size distributions and impedance tube measurements of excised samples. Acoustic transmission loss predicted by the proposed model is compared with data. The surface impedance of the sand is modelled with an increasing degree of complexity and this study shows the impact that such added complexity has on the prediction of transmission loss.

Seismic and acoustic signals can be produced by both above- and below-ground explosions and are often observed at long propagation ranges. In the case of a below ground explosion, seismic waves displace the surface producing acoustic signals that can be understood using a Rayleigh integral analysis. Combining this Rayleigh integral analysis with a seismic model for the ground motion produced by a specified emplacement (i.e., depth and explosive yield) enables estimation of the acoustic signal produced by a specific source scenario. A seismoacoustic model describing the infrasonic signals produced by underground explosions will be presented and predictions will be compared with observations from the Source Physics Experiment (SPE) at distances of a few kilometers. This source model will be combined with statistical propagation models accounting for atmospheric variability as well as wind noise estimates to identify those emplacements and propagation scenarios for which regional distance signals are likely to be observable.

The propagation of signals from elevated sources in the lower audio band (30–500 Hz) are simulated and processed to obtain angle of arrival (AOA) estimates using a small acoustic array. The propagation of the signals are simulated using ray tracing through a stratified atmosphere that is implemented with a finite difference time domain method described by Pierce. The wind and temperature profiles are modeled using Monin-Obukhov similarity theory. The ground reflection is modeled using a two-parameter ground impedance model developed by Attenborough. The spatial coherence of the signals at the array are handled using a statistical model developed by Kozick et al. Basically, the coherence at difference microphones is reduced based upon the range of the source and distance between microphones. The source is modeled using a harmonic structure with no atmospheric or spherical attenuation. This is reasonable since the amplitude of sources is often not known. The AOA of the simulated signals are estimated using several beamforming algorithms and analyzed.

In this work, Green’s function retrieval and frequency-wavenumber methods are employed to enhance array plane-wave beamforming maps for acoustic source localization and range estimation in an outdoor environment. The crosscorrelation and multidimensional deconvolution Green’s function retrieval methods are used to improve the signal-to-noise ratio of the beamforming maps. The Stolt’s frequency-wavenumber migration method is adapted to the plane-wave beamforming map to find the source positions, applying frequency-wavenumber migration image to the Stolt spatial transformation mapping. Open field microphone array measurements of active and passive sources are investigated. Of particular interests are the accuracy of the estimated source position, the effects of multiple sources and the image contrast of the beamforming maps.

In this work, an analytical expression is sought for the sound pressure of aircraft wake vortices near a ground surface. The analytical basis for the mechanisms of aircraft vortex sound generation follows the vortex dynamic models and vortex sound theory. The theory focuses on acoustic signatures of the vortex created from subsonic flow. Vortex acoustic signature from a ground can mainly be characterized based on the boundary condition and transition of the flow moving away from the ground. Of interest is acoustic characterization of wake vortices in ground effect. To this end, the method of images was used to simulate the presence of the ground. The method of images assures that the vorticity is mirrored about the ground plane that contributes to the modified amplitude above the ground. The extension of the presented approach to model the turbulent flow in the ground effect will also be highlighted.

In the context of sustainable energies, wind energy plays a major role. However, the expansion of wind energy is contrasted with a sometimes bad acceptance of the nearby living population as well as the shortage of profitable sites. Accordingly, there is increasing emphasis on installing wind turbines in more complex terrain, requiring knowledge concerning the efficiency of the plant but also its noise impact with respect to the surrounding topography. Within the NEWA-project, the influence of atmospheric conditions, topography and soil conditions were investigated. The physical processes involved are complex, frequency dependent and interact with each other. Depending on the atmospheric conditions, significant differences in the attenuation of 15 dB and more for distances larger than 500 m from the source can be observed. The aim of this talk is to show, how the influence of different meteorological conditions in combination with the complex terrain on sound propagation can be analyzed and particularly loud situations can be identified. It will be shown how long term, high-resolution data that were measured in topographically structured terrain can be analyzed to allow a detailed view on the meteorological conditions involved in this process with particular attention drawn to the influence of terrain features.

It can be expected that the noise emission of wind turbines (WT) is closely correlated with the noise emission at a remote location. Nevertheless, monitoring the noise emission level of wind turbines is difficult because the local noise level is determined by a variety of influences. On the one hand, there is the very variable emission level, depending on the inflow conditions, the rotational speed and the operative state of the turbine. On the other hand, the specific assignment of the noise to the source is difficult because the emission level is often at the level of the extraneous noise. To improve the understanding of the sound transmission under different meteorological conditions, such an assignment of the sources noise is essential. The aim of this talk is to show how sufficient high resolution (temporal and spectral) long-term measurement data can be evaluated to obtain information on noise emission, rotational speed, background noise, amplitude modulation and local noise exposure from a wind turbine. For this purpose, data will be used that have been recorded over a period of 40 days with a resolution of 10Hz and at five locations at different distances from the WT in complex terrain while at the same time documenting very accurately the flow conditions and meteorology.

Within the project "WEA Akzeptanz" five extensive measurement campaigns were conducted under various environmental conditions, including the detection of acoustical, meteorological, and wind turbine performance data at high resolution. The campaigns differ in terms of measurement locations, time of the year, and distances of the acoustic measurement stations to the turbine. The first two aspects imply different wind turbine types with specific acoustic properties as well as different topographic and meteorological conditions. The latter point is essential for the measurement-based investigation of sound propagation from wind turbines. In the measurement campaigns, distances of 150 to 1100m to the wind turbine were realized. In this contribution, an overview of the measurements carried out and the measurement setup is first given. In addition, the acquisition, processing, and analysis of the data are presented. Herein the focus is on the acoustical data. Using the example of one measurement campaign, the classification of the data sets is described, and finally, the influence of different sound speed gradients on sound propagation is shown. For selected sound speed profiles, the measured sound pressure levels and one-third octave spectra are discussed in relation to the distance to the wind turbine.

The atmospheric sound propagation is strongly influenced by prevailing weather conditions. Geometrical effects like geometric refraction associated to wind gradients and scattering of sound waves due to atmospheric turbulence occur in atmospheric sound propagation. Accordingly, sound levels at an emission point in long-range sound propagation are also strongly affected and show high variability. The Parabolic Equation (PE) Method is chosen for calculating atmospheric sound propagation. The probabilistic studies of sound emissions in previous investigations showed that a lognormal probability distribution describes the sound pressure levels occurring at an emissions point. To describe the turbulent atmosphere, the Gaussian spectrum is used. Based on these investigations, the von Kármán spectrum is used in this work to describe atmospheric turbulence. The variation of the input parameters, such as wind speed variations, is investigated. Consequently, information about the sound pressure level at the emission is obtained and examined. The probability of occurrence of sound pressure levels is quantified to predict the sound emission under complex atmospheric conditions.

In seismology, the depth of a near-surface source is hard to estimate in the absence of local stations. The depth-yield trade-off leads to significant uncertainties in the source's depth and strength estimations. Long-range infrasound propagation from an underwater or underground source is very sensitive to variations in the source's depth and strength. This characteristic is employed in an infrasound-based inversion for the submerged source parameters. Firstly, a Bayesian inversion scheme is tested under the variations of the number of stations, the signal’s frequency band, and the signal-to-noise ratio (SNR). Secondly, an ensemble of realistic perturbed atmospheric profiles is used to investigate the effect of atmospheric uncertainties on the inversion results. Results show that long-range infrasound signals can be used to estimate the depth and strength of an underwater source. Using a broadband signal proved to be a fundamental element to obtain the real source parameters, whereas the SNR was secondary. Regardless of the number of stations, their positions, and SNRs, all of the estimated depths were within 10% from the real source depth while the source strength uncertainties can go up to 50%.

The propagation of sonic boom is studied within the EU project RUMBLE, which aims at providing expertise to support the definition of new regulations on noise due to supersonic civil flight. Sonic boom propagation in the presence of atmospheric turbulence, temperature gradients and irregular terrain is notably investigated. Advances have been made regarding meteorological effects, but few studies have tackled the problem of ground effects. The reflected boom is classically obtained by multiplying by a constant factor the incident boom, which is reflected on a flat perfectly reflecting surface. The objective of the present study is to take into account the impact of irregular terrain on sonic boom propagation and to access its significance. Numerical methods making use of high-order finite difference schemes are used to solve the two-dimensional Euler equations. The impact of different types of irregular terrain on sonic boom propagation is analyzed. Their effect on a classical N-wave is explored, as well as on low boom signatures. Pressure fluctuation fields and waveform variability are investigated, along with the sound perceived at ground level using metrics sensitive to different frequency content. [This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N769896 (RUMBLE). In addition, this work is supported by RSF-17-72-10277 and by the Labex CeLyA of Université de Lyon, operated by the French National Research Agency (ANR-10-LABX-0060/ANR-11-IDEX-0007)].

Sound waves are randomly scattering by turbulence and other atmospheric variations. Statistical distributions for the scattered signals are important for applications involving signal detection and classification. Many single-variate distributions have been considered for the signal power at a single receiver, including log-normal, exponential, chi-square, gamma, and Rician. The appropriateness of the distribution depends on the scattering strength and the signal averaging. The options for multivariate distributions, as needed to model signals at an array of receivers, are much more limited. Primarily, there is the complex multivariate log-normal distribution, which can be used for the signal power in weak scattering, and the complex Wishart distribution, which can be used for strong scattering and is essentially a multivariate generalization of the chi-squared distribution. The matrix gamma distribution generalizes the Wishart and may also be appropriate for weak scattering. Since sound signals in the atmosphere are typically strongly scattered, the Wishart distribution appears to be particularly useful. Some simple examples are provided to demonstrate the impact of random signal scattering in classification problems. The examples show how the robustness of the classifier improves through incoherent averaging, and how a full Bayesian classifier based on the Wishart distribution outperforms a naïve Bayesian classifier which assumes that the sensor data are independent.

In many situations, windscreens made of a porous material are used to reduce noise from wind incident on a pressure sensor. The mechanism for noise reduction is often described as a spatial averaging effect. Since the coherence of turbulence decreases with increasing spatial displacement, at scales smaller than the windscreen, the fluctuations over the screen surface will combine with only partial coherence. A theory for wavevector pressure spectra within an arbitrary, finite-volume windscreen produced by a homogeneous stagnation field is formulated. The windscreen is considered as nearly impermeable, such that the interior is quiescent. It is shown that the wavevector pressure spectrum can be expressed as the product of the homogeneous stagnation field spectrum with a weighting function, which is only a function of the windscreen geometry. To illustrate, particular results are derived for spherical and cylindrical windscreens, and one-dimensional spectra are produced through numerical integration. It is shown that the windscreen acts to filter wavenumbers which correspond with dimensions smaller than its own. These results are used to elucidate the discrepancies in windscreen performance observed between wind tunnel and atmospheric measurements. Potential inaccuracies and approaches for including flow distortion around the windscreen are discussed.

Accurate characterization of the environment is essential for robust predictions of infrasound propagation. In particular, meteorological data often exhibit large spatiotemporal variations, making accurate characterization challenging. Although numerical weather models can provide realistic representations of the meteorological environment, the spatial and temporal sampling frequencies needed for accurate prediction of infrasound propagation are currently unknown. To address this issue, simulations were conducted with the Weather Research and Forecasting (WRF) meteorological model, and the output was incorporated into a wide-angle parabolic equation method (PE) model to predict local infrasound propagation (< 150 km) for frequencies up to 20 Hz. The sensitivity of infrasound propagation to spatial (1, 15, and 150 km) and temporal (0 - 60 s) sampling frequency within the WRF model was then calculated. The results for both stable (nighttime) and unstable (daytime) atmospheres are discussed, with particular attention to comparisons vs. static atmospheric conditions. [This work was funded by the Assistant Secretary of the Army (Acquisition, Logistics, and Technology) [ASA(ALT)] with portions funded under 0602784/T40/24 and 0602146/AR9/01.] Distribution Statement A: Approved for public release; Distribution is unlimited.

The narrow-angle parabolic equation (NAPE), with the effective sound speed approximation (ESSA), is widely used for sound and infrasound propagation in a moving medium such as the atmosphere. However, it is valid only for angles less than 20 deg with respect to the nominal propagation direction. In this presentation, the wave equation and extra-wide-angle parabolic equation (EWAPE) for high-frequency sound waves in a moving medium with arbitrary Mach numbers are derived without the ESSA. For relatively smooth variations in a moving medium, the EWAPE is valid for propagation angles up to 90 deg. Using the Padé (n,n) series expansion and narrow-angle approximation, the EWAPE is reduced to the wide-angle parabolic equation (WAPE) and NAPE. Versions of these equations are then formulated for low Mach numbers, which is the case usually considered in the literature. The phase errors pertinent to the equations considered are studied. It is shown that the equations for low Mach numbers and the WAPE with the ESSA are applicable only under rather restrictive conditions on the medium velocity. An effective numerical implementation of the WAPE for arbitrary Mach numbers in the Padé (1,1) approximation is developed and applied to sound propagation in the atmosphere.