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BACKGROUND: Community initiatives to promote physical activity in children are common, but evidence supporting their effectiveness is limited. OBJECTIVES: To examine the relationships between community programs and policies and children’s physical activity in a large and diverse sample of U.S. communities. METHODS: Programs and policies to promote children’s physical activity were assessed in 130 communities by key informant interviews, and physical activity behaviors were measured by self- and parental-report in samples of children in each community (total n = 5138). Associations between composite indices of community programs and policies and indicators of total and moderate-to-vigorous physical activity were examined without and with adjustment for demographic factors. RESULTS: An index reflecting the six-year history of the number of behavior change strategies used in community programs and policies was positively associated with children’s moderate-to-vigorous physical activity. This association was attenuated with adjustment for demographic factors. Effect modification analyses found that the association was positive among non-Hispanic children, but was negative for Hispanic children. CONCLUSIONS: Community initiatives to promote physical activity in children were positively associated with children’s physical activity in non-Hispanic children. Such initiatives were negatively associated with physical activity in Hispanic children, suggesting that future research should consider unique cultural factors when designing community initiatives to promote activity in this population sub-group.

Understanding infrasound propagation is important for geophysical and military applications. Infrasound signatures can be detected from larger sources such as nuclear detonations and from smaller sources such as bridges, dams, and buildings. Infrastructure sources produce signals of lower amplitude, leading to more regional (up to 150 km) propagation. However, current methods for calculating regional infrasound propagation involve assumptions about the atmosphere, such as horizontal homogeneity, that deviate from more realistic environmental conditions and decrease the accuracy of the infrasound predictions. To remedy this issue, we have interfaced three-dimensional forecasts from the Weather Research and Forecasting (WRF) meteorological model with range-dependent parabolic equation propagation models. To test the improvement of infrasound propagation predictions with more realistic weather data, we conducted sensitivity studies with different propagation ranges and horizontal resolutions and compared the...

An overview is provided of multilevel modeling of community noise annoyance. By multilevel, it is meant that noise exposure and noise tolerance vary on the community level, and among individuals within the communities. Although these assumptions are rather simple, they lead to a rigorous statistical model with characteristics consistent with noise survey data. Regression analyses with a multilevel, generalized linear model (GLM) enable the model parameters and their variations at the community and individual levels to be distinguished and quantified. Based on a meta-analysis of transportation noise, the community-level and individual-level noise tolerance variances are both evident, although the individual-level variance is stronger. The significance of community-level variance is consistent with the recently introduced concept of community tolerance level (CTL). Although the multilevel model describes and quantifies the community-level variations, it does not by itself explain why communities differ, or how to account for these differences in regulations. Future research should address the relationships between community tolerance variations and factors such as soundscape disturbance and attitude toward the most prominent noise sources.An overview is provided of multilevel modeling of community noise annoyance. By multilevel, it is meant that noise exposure and noise tolerance vary on the community level, and among individuals within the communities. Although these assumptions are rather simple, they lead to a rigorous statistical model with characteristics consistent with noise survey data. Regression analyses with a multilevel, generalized linear model (GLM) enable the model parameters and their variations at the community and individual levels to be distinguished and quantified. Based on a meta-analysis of transportation noise, the community-level and individual-level noise tolerance variances are both evident, although the individual-level variance is stronger. The significance of community-level variance is consistent with the recently introduced concept of community tolerance level (CTL). Although the multilevel model describes and quantifies the community-level variations, it does not by itself explain why communities differ, or ...

The possibility of designing a porous medium that mimics an acoustical perfectly matched layer (PML) is discussed. In numerical methods, a PML provides essentially zero reflection and rapid attenuation in space. As a starting point to designing such a medium, the relaxation-model equations (10.54) and (10.55) from V. E. Ostashev and D. K. Wilson [Acoustics in Moving Inhomogeneous Media, CRC Press, Boca Raton, 2016] are employed. In general, it does not appear to select the parameters to mimic a PML across a range of frequencies. For relatively high frequencies, however, it is shown that by setting the ratio of the vorticity and entropy shape factors to (Npr)1/2 /(γ-1), where Npr is the Prandtl number and γ is the ratio of specific heats, the impedance becomes real-valued while the medium remains attenuative. Possible approaches are discussed for adjusting this ratio based on varying the pore shape, the cross section, and the pore-size distribution. However, it does not appear to be possible to make the ratio less than one, as would be necessary to realize the PML condition in air and other fluids.

Sound waves propagating through the atmosphere and ocean are randomly scattered by turbulence, internal waves, surface roughness, and other processes. In some limiting cases, probability density functions (pdfs) for the scattered signal variations can be derived, e.g., the log-normal pdf for weak scattering (in the Rytov approximation) and the exponential pdf for strong scattering. A variety of more general, usually empirically based, distributions are available which reduce to these limiting cases, such as the Rice, gamma, and generalized gamma. For situations involving multiple receivers, multivariate log-normal, Wishart, and matrix gamma pdfs may be employed. Parametric uncertainties and spatial/temporal variability in the scattering process can be addressed with a compound pdf formulation, which involves an additional distribution for the uncertain or variable parameters. From a Bayesian perspective, the scattering pdf corresponds to the likelihood function, the pdf for the uncertain parameters to the prior/posterior, and the compound pdf to the marginal likelihood. Many common scattering pdfs possess Bayesian conjugate priors, which lend themselves to simple updating equations and analytical solutions for the posteriors and marginal likelihoods. This presentation summarizes important pdfs for randomly scattered signals and their conjugate priors when available.

Comprehensive modeling of sound propagation through the atmospheric boundary layer is viewed as a judicious combination of accurate computational mechanics models and uncertainty quantification (UQ) methods. The role of numerical models is to represent nominally deterministic phenomena, e.g., geometrical spreading, ground interactions, refraction by mean gradients of wind and temperature. The role of UQ is to characterize the consequences of fundamentally non-deterministic and imprecisely known factors that affect propagation, e.g., turbulence in the atmospheric boundary layer, complex terrain features, and overly sparse spatio-temporal sampling of propagation parameters. High-fidelity wave propagation mechanics cannot compensate for inherent randomness in the environment and insufficient data on the parameters. When uncertainty is significant, the computational cost of high-fidelity models might be better invested in more ensemble simulations with medium-fidelity models and quantifying the payoff from more data about the environment. Work in recent years along three thrusts to enable this form of comprehensive modeling is reviewed: (1) Surrogate modeling based on cluster-weighted models, which are a type of probabilistic generative model, and on statistical learning methods, (2) global sensitivity analysis for assessing the importance of model parameters, and (3) a computational mechanics error budget for rationally analyzing the importance of various sources of uncertainty.Comprehensive modeling of sound propagation through the atmospheric boundary layer is viewed as a judicious combination of accurate computational mechanics models and uncertainty quantification (UQ) methods. The role of numerical models is to represent nominally deterministic phenomena, e.g., geometrical spreading, ground interactions, refraction by mean gradients of wind and temperature. The role of UQ is to characterize the consequences of fundamentally non-deterministic and imprecisely known factors that affect propagation, e.g., turbulence in the atmospheric boundary layer, complex terrain features, and overly sparse spatio-temporal sampling of propagation parameters. High-fidelity wave propagation mechanics cannot compensate for inherent randomness in the environment and insufficient data on the parameters. When uncertainty is significant, the computational cost of high-fidelity models might be better invested in more ensemble simulations with medium-fidelity models and quantifying the payoff from mo...

Meteorological conditions in an arctic environment differ significantly from those in a temperate environment. Atmospheric phenomena particular to polar regions, including wind patterns such as the polar vortex and low-level jets above strongly stable layers, strong temperature and humidity gradients, and density currents, could have unique impacts on infrasound propagation that are not observed in temperate locations. In this study, parabolic-equation simulations of sound propagation are performed using measured meteorological conditions for summer and winter conditions in temperate and arctic locations. The similarities and differences in environmental conditions between these two locations and their relative impact on the predicted transmission loss are examined. For summer conditions, a comparison to measured data from explosive sources is performed for both temperate and arctic locations.

Tolerance to noise varies between communities, and between individuals comprising the communities. A multilevel modeling approach is useful for capturing such individual- and community-level variations. Here, we consider a model in which the community-level variations are sampled explicitly with community noise surveys, while the individual-level variations are sampled only in a statistical sense (i.e., hidden). The community-level variations are specifically quantified by the community tolerance level (CTL) [Fidell et al., J. Acoust. Soc. Am. 130(2), 791-806 (2011)]. Simulations based on the multilevel model indicate that the community- and individual-level variations have distinct statistical signatures, both of which are evident in noise annoyance surveys involving transportation noise. The annoyance curve for a previously unsurveyed community depends on the mean and variance of the CTL, and the sum of the hidden variances in noise tolerance and exposure among individuals in the community. Regression a...

In this paper, numerical simulations are used to study the turbulent wind noise reduction effect of microphone windscreens with varying shapes and flow resistivities. Typical windscreen shapes consisting of circular, elliptical, and rectangular cylinders are investigated. A turbulent environment is generated by placing a solid circular cylinder upstream of the microphone. An immersed-boundary method with a fifth-order weighted essentially non-oscillatory scheme is implemented to enhance the simulation accuracy for high-Reynolds number flow around the solid cylinder as well as at the interface between the open air and the porous material comprising the windscreen. The Navier-Stokes equations for incompressible flow are solved in the open air. For the flow inside the porous material, a modified form of the Zwikker-Kosten equation is solved. The results show that, on average, the circular and horizontal ellipse windscreens have similar overall wind noise reduction performance, while the horizontal ellipse windscreen with medium flow resistivity provides the most effective wind noise reduction among all the considered cases. The vertical ellipse windscreen with high flow resistivity, in particular, increases the wind noise because of increased self-generation of turbulence.

A general problem is considered in which a source of unknown power transmits to multiple receiver locations. The signal is randomly scattered along each transmission path, for example, by turbulence, a forest, or buildings. At each receiver location, one or more observations of the signal power are collected. It is assumed that the functional form of the probability density function (pdf) of the received signals (an exponential pdf for strong scattering, or a gamma pdf for weak scattering) is known based on an understanding of the scattering process, although the mean transmission losses (TLs) from the source to receivers are uncertain. From the signal observations, we wish to estimate the mean power of the source and the mean TLs for each path. A Bayesian formulation for this problem is presented. An inverse gamma prior is used for the TL, which is the conjugate prior for the exponential or gamma scattered signal pdf (likelihood function). Analytical solutions are then derived for a number of limiting scenarios: (1) unscattered signals along multiple paths with dependent TLs, (2) strongly scattered signals along multiple paths with the same TL, and (3) weakly or strongly scattered signals along multiple paths with independent TLs.A general problem is considered in which a source of unknown power transmits to multiple receiver locations. The signal is randomly scattered along each transmission path, for example, by turbulence, a forest, or buildings. At each receiver location, one or more observations of the signal power are collected. It is assumed that the functional form of the probability density function (pdf) of the received signals (an exponential pdf for strong scattering, or a gamma pdf for weak scattering) is known based on an understanding of the scattering process, although the mean transmission losses (TLs) from the source to receivers are uncertain. From the signal observations, we wish to estimate the mean power of the source and the mean TLs for each path. A Bayesian formulation for this problem is presented. An inverse gamma prior is used for the TL, which is the conjugate prior for the exponential or gamma scattered signal pdf (likelihood function). Analytical solutions are then derived for a number of limiting sc...

Acoustic pulse propagation through forests is important for many applications, including noise attenuation by stands of trees, and localization of sound sources. Due to the highly complicated distribution of trees in natural forests, it is appropriate to consider a forest as a continuous distribution of scatterers of various shapes and sizes. A propagation model based on radiative transfer theory under a modified Born approximation may be developed for this situation to describe both the coherent and diffuse sound propagation . The simple case of an impulse in an infinite homogeneous forest of diffuse scatterers is first considered, and then the effects of successively including non-diffuse scatterers, ground reflections in a forest of finite height, and, finally, a realistic forest model are analyzed. These theoretical findings are then compared with experimental results. Lastly, a numerical example describing the effect of a forest on a simple beamforming array is considered.Acoustic pulse propagation through forests is important for many applications, including noise attenuation by stands of trees, and localization of sound sources. Due to the highly complicated distribution of trees in natural forests, it is appropriate to consider a forest as a continuous distribution of scatterers of various shapes and sizes. A propagation model based on radiative transfer theory under a modified Born approximation may be developed for this situation to describe both the coherent and diffuse sound propagation . The simple case of an impulse in an infinite homogeneous forest of diffuse scatterers is first considered, and then the effects of successively including non-diffuse scatterers, ground reflections in a forest of finite height, and, finally, a realistic forest model are analyzed. These theoretical findings are then compared with experimental results. Lastly, a numerical example describing the effect of a forest on a simple beamforming array is considered.

One of the primary challenges for performing robust automated target recognition (ATR) is how to compensate the signatures for environmental propagation effects. ATR algorithms tend to function well only in the specific terrain and atmospheric conditions for which they were trained. This is particularly true for acoustic signals, which undergo strong frequency-dependent scattering and refraction in both outdoor and underwater environments. To address this problem, we formulate a Bayesian sequential updating method, which accounts for realistic signal and noise distributions, and uncertainties in the parameters of these distributions. The formulation utilizes physics-based scattering models for signal fading and the cross coherence between frequencies and transmission paths. We discuss how, in a Bayesian context, the scattering models correspond to likelihood functions, which are conveniently paired with their conjugate priors to efficiently update the uncertain signal parameters (hyperparameters). The ori...

Accurate atmospheric infrasound propagation models must account for variations in local sound speed and ambient flow. This paper describes and demonstrates a method to extend the Green’s function parabolic equation (GFPE) to account for 3D high Mach number ambient flow in addition to an inhomogeneous atmosphere. Predictions of infrasonic propagation using the resulting GFPE model are then compared with predictions using other models.

DOI: 10.2514/1.44288 Atmospheric turbulence has significant influences on both the trajectories and strengths of wake vortices. In this paper, a quasi-wavelet method is used to generate a random atmospheric turbulence field based on the von Karman spectrum, in which atmospheric turbulence is represented by groups of random eddies. An inviscid wake vortex system, out-of-ground effect or in-ground effect, is immersed in the generated turbulence background to study the effects of random turbulence on wake vortices. The simulated wake trajectories are compared with literature data from several current prediction models as well as from field measurement.

Quasi-wavelets (QWs) are eddy-like entities similar to customary wavelets in the sense that they are based on translations and dilations of a spatially localized parent function. The positions and orientations are, however, normally taken to be random. Random fields such as turbulence may be represented as ensembles of QWs with appropriately selected size distributions, number densities, and amplitudes. This paper overviews previous results concerning QWs and provides a new, QW-based model of anisotropic turbulence in a shear-dominated surface layer. The following points are emphasized. (1) Many types of QWs and couplings, suitable for various applicatons, can be constructed through differentiation of spherically symmetric parent functions. For velocity fluctuations, QWs with toroidal and poloidal circulations can be derived. (2) Self-similar ensembles of QWs with rotation rates scaling according to Kolmogorov's hypotheses naturally produce classical inertial-subrange spectra. (3) Momentum and heat fluxes in surface-layer turbulence can be described by introducing preferred orientations and correlations among QWs representing temperature and velocity perturbations. (4) In contrast to Fourier modes, QWs can be naturally arranged in a spatially intermittent manner. Models for both local (intrinsic) and global intermittency are discussed. (5) The spatially localized nature of QWs can be advantageous in wave-scattering calculations and other applications.

Acoustic tomography of the atmospheric surface layer (ASL) is based on travel-time measurements between speakers and microphones in a spatial array, which are arranged so as to create propagation paths through the region to be sampled. Then, the temperature and wind velocity fields inside the tomographic region are reconstructed by inverting the travel times. Tomography has certain advantages over conventional point measurements, such as spatial averaging and a quadratic growth of the observations relative to the number of sensors. An array built at the Boulder Atmospheric Observatory (BAO) enables horizontal-slice tomography of the ASL at a height of 8 m above the ground, in an 80 m x 80 m region. The instrumentation and principle of operation of the BAO tomography array are explained. Inverse algorithms for reconstruction of the temperature and wind velocity fields from the travel times are reviewed. Results in numerical simulations of the BAO tomography array and reconstruction of turbulence fields in ...

The performance bounds of a passive acoustic array operating in a turbulent medium with fluctuations described by a von Kármán spectrum are investigated. This treatment considers a single, monochromatic, plane-wave source at near-normal incidence. A line-of-sight propagation path is assumed. The primary interests are in calculating the Cramer-Rao lower bounds of the azimuthal and elevational angles of arrival and in observing how these bounds change with the introduction of additional unknowns, such as the propagation distance, turbulence parameters, and signal-to-noise ratio. In both two and three dimensions, it is found that for large values of the index-of-refraction variance, the Cramer-Rao lower bounds of the angles of arrival increase significantly at large values of the normalized propagation distance. For small values of the index-of-refraction variance and normalized propagation distance, the signal-to-noise ratio is found to be the limiting factor. In the two-dimensional treatment, it is found that the estimate of the angle of arrival will decouple from the estimates of the other parameters with the appropriate choice of array geometry. In three dimensions, again with an appropriate choice of array geometry, the estimates of the azimuth and elevation will decouple from the estimates of the other parameters, but due to the constraints of the model, will remain coupled to one another.

Previous reports have emphasized the requirements for strong type 1 cell-mediated responses in the control of human immunodeficiency virus type 1 (HIV-1). HIV-1 Gag p24-specific CD4 helper T-lymphocyte (HTL) responses have been shown to inversely correlate with viral burden in HIV-1-infected individuals. In this study, peripheral blood mononuclear cells from 70 individuals with chronic progressive HIV-1 infection (clinical progressors), 10 clinical nonprogressors, and 3 immunologically discordant progressors were assessed for HTL proliferation and type 1/type 2 cytokine production. Clinical progressors lacked functional HIV-1-specific HTLs with proliferative and cytokine-producing capacity. Clinical nonprogressors were found to respond to a wide range of HIV-1 antigens from different clades, producing both type 1 and type 2 cytokines. Immunologically discordant progressors responded strongly to clade B Gag p24 with a type 1 cytokine profile but not to other antigens. Thus, in contrast to clinical nonprogressors, neither progressors nor immunologically discordant progressors secreted interleukin-4 (IL-4) in response to HIV-1 antigens. Both clinical nonprogressors and immunologically discordant progressors responded broadly to B clade Gag p24-overlapping peptides. However, IL-4 production in the nonprogressors was restricted to a limited number of p24 peptides. No HIV-1-specific T-cell responses were seen in 20 seronegative controls. Additionally, we observed a rapid type 1 to type 2 shift in the response of one immunologically discordant progressor upon onset of clinical symptoms. These results suggest that a balanced type 1/type 2 profile correlates with successful long-term control of HIV-1.

In this study, we compared human immunodeficiency virus (HIV) type 1-specific proliferative responses with HIV-1-induced intracellular cytokine production in a cohort of clinically nonprogressing patients and individuals with progressive HIV-1 infection. We found strong HIV-1-specific proliferative responses in the clinical nonprogressor cohort that correlated with significant numbers of circulating HIV-1-specific CD4(+) T cells. In contrast, HIV-1-specific proliferative responses were absent in most individuals with progressive HIV-1 infection, even though interferon-gamma-producing HIV-1-specific CD4(+) T cells were detectable by flow cytometry. The implication of these data is that the important dysfunction seen in most HIV-positive patients from very early in disease may be an inability of HIV-1-specific CD4(+) memory T cells to proliferate in response to HIV antigens rather than an absolute loss of circulating virus-specific CD4(+) T cells.

The impact of atmospheric turbulence on sound propagation is an important consideration for source localization with acoustic sensor arrays, studies of noise pollution, and the development of new remote sensing techniques. This paper takes as a starting point a recently derived, closed-form equation for the spatial-temporal coherence function of a broadband acoustic signal propagating in a refractive, turbulent atmosphere with spatial-temporal fluctuations in temperature and wind velocity. The theory is quite general and enables analysis of many statistical characteristics of the sound field. It has certain advantages in comparison with Monte-Carlo simulations and has already been used to study the spatial-temporal coherence of narrowband signals. In the present paper, this theory is employed to calculate and analyze the frequency decorrelation of broadband acoustic signals for different regimes of the atmospheric surface layer. The results are then used to study the effect of atmospheric turbulence on the mean intensity of an acoustic pulse.

Several approaches have been used in the literature to characterize sound scattering in forests. In this presentation, an approach based on the radiative transfer equation (RTE) is considered. Although the RTE has been used for other types of scattering problems, it is new to forest acoustics. The RTE is an integro-differential equation for the specific intensity, which is the average power flux density within a unit solid angle in a certain direction of propagation. It describes the processes of sound scattering and absorption by discrete scatterers such as tree trunks, branches, and leaves. RTE is applied to sound propagation in a four-layer forest model (ground, trunks, canopy, and open air). The trunk layer is modelled with vertical cylinders, while the canopy layer is modeled by spheres. The scattering amplitudes and total scattering cross sections of these scatterers are identified. At the interface of the trunk layer and ground, the specific intensity is specularly reflected. Although the RTE is ba...

Uncertainties in source characteristics, meteorological conditions, and topographic variations present formidable challenges for accurately predicting long-range outdoor sound propagation. Numerical propagation models inherently assume perfect knowledge of these uncertain variables and are fixed in a modeling sense. In contrast, statistical learning models can incorporate new observations to update the underlying prediction model. Past work has shown that statistical learning models trained on synthetic data for predicting long-range sound propagation have, at best, an overall root-mean-square error (RMSE) of about 5 dB. This limit appears to be imposed by modeled atmospheric turbulence. It is hypothesized that this prediction limit may be lowered as observational data are incorporated into trained statistical learning models. Furthermore, data are assimilated by a Kalman filtering process for the purpose of updating knowledge of the atmospheric and source characteristics. Within the prediction phase thre...

The acoustic spectrum emitted by unmanned aerial vehicles (UAVs) and other aircraft can be distorted by propagation through atmospheric turbulence. Since most UAVs are propeller-based, they generate a series of acoustic tones and harmonics. In this paper, spectral broadening of these tones due to atmospheric turbulence is studied. The broadening results from the combined Doppler effect of multiply scattered acoustic signals propagating in a non-stationary turbulent atmosphere. It can be assessed as a Fourier transform of the temporal coherence function of a monochromatic signal propagating in an atmosphere with spatial-temporal fluctuations in temperature and wind velocity. This temporal coherence was recently investigated [V. E. Ostashev, D. K. Wilson, S. N. Vecherin, and S. L. Collier, J. Acoust. Soc. Am. 136 (5), 2414–2431 (2014)] for the model of locally frozen turbulence. Based on these results, spectral broadening is calculated and analyzed for typical meteorological regimes of the atmospheric bound...

Large scatter in community noise annoyance survey data has recently been linked to systematic variations in noise tolerance. We hypothesize that noise tolerance is related to secondary factors, including environmental (e.g., population density, ambient noise) and attitudinal (e.g., noise sensitivity). If noise tolerance and secondary factors can be linked, the secondary factors provide a means to generalize noise annoyance from surveyed communities to non-surveyed communities. This approach would be useful for generalizing annoyance caused by quiet supersonic flight or military blast noise from a limited number of surveyed communities to other locations. A simple multilevel modeling approach (D.K. Wilson, et al. “Community noise annoyance: Connecting regression methodologies and theoretical models,” J. Acoust. Soc. Am. 139(4), 1983 (2016)) offers a useful framework to study the relationship between noise tolerance and secondary factors. The framework has already been applied to historic survey data on tra...

Wind-induced noise, as sensed by a screened microphone in the atmosphere, produces a highly varying noise floor. At low frequencies, this noise source may dominate the ambient noise spectrum and present a challenge for signal detection. The sensed noise is affected by several factors in the atmospheric convective boundary layer: the mean flow at the height of the microphone, turbulent eddy interaction with the windscreen, and pressure fluctuations within the turbulent flow. Recently, van den Berg (2006) compared measured wind noise to modeled spectra. In that study, several meteorological variables were inferred from fits of modeled wind noise spectra rather than from meteorological observations. If additional meteorological observations are collected, then it may be possible to conduct model validation. In addition to temperature, pressure, and wind velocity, the surface roughness length for momentum and the vertical temperature flux must be observed. Recent models of turbulent wind velocity, in the conv...

Although the fundamental physics of sound propagation outdoors (e.g., absorption, ground interactions, refraction, and scattering) are well understood, modeling capabilities are typically inadequate to capture the many intricate interactions with the atmosphere, ground, and natural and man-made terrain features. Furthermore, environmental data are rarely available at the sub-wavelength resolution needed to accurately predict the sound field in the audible range, in a deterministic sense. Fortunately, advances in computing capabilities and statistical sampling methods provide new opportunities for quantifying the inherent uncertainties of sound propagation predictions. Among the sampling techniques considered in this presentation are ordinary Monte Carlo sampling, Latin hypercube sampling, stratified sampling based on meteorological classes, importance sampling, and adaptive importance sampling. When uncertainties in the atmospheric and ground properties dominate, importance sampling is found to converge t...

A new, rigorous theory of acoustic pulse scattering in a turbulent atmosphere with spatial-temporal fluctuations in temperature and wind velocity is developed. The theory generalizes the classical theory of sound scattering to broadband signals and coupled spatial-temporal fluctuations of random fields. The scattered sound field is obtained as a Born approximation of a set of equations for the sound pressure and acoustic particle velocity. The spatial-temporal correlation function of the scattered field is calculated. These results are obtained without using the quasi-static approximation, which is employed in the classical theory, and enable analysis of this approximation. The spatial, temporal, and frequency coherences of the scattered signal are studied. The results obtained are applied to acoustic remote sensing of the atmosphere with sodars. It is proposed that the frequency spectrum of the temporal correlation function could be used to measure the wind velocity and the variance of the convective vel...

Acoustic sensors are being employed on airborne platforms for localization of sources on the ground. In this presentation, the impact of atmospheric turbulence and refraction of sound signals due to the vertical profiles of temperature and wind velocity on source localization are overviewed. The variance of the angle of arrival of sound signals in a turbulent atmosphere is analyzed. A theory is presented which accounts for refraction corrections in source localization with elevated sensor arrays. The theory expresses the horizontal, azimuthal, and elevation refraction corrections in terms of the vertical profiles of temperature and wind velocity and the sensors’ coordinates. The theory is applied to the results of a comprehensive experiment in source localization with an aerostat-mounted acoustic sensor array at Yuma Proving Ground (YPG). Long term atmospheric data sets from weather modeling systems are used for a climatological assessment of the refraction corrections and localization errors. Due to reci...

Long-range outdoor sound propagation is characterized by a large variance in sound pressure levels due to factors such as refractive gradients, turbulence, and topographic variations. While conventional numerical methods for long-range propagation address these phenomena, they are costly in computational memory and time. In contrast, machine-learning algorithms provide very fast predictions, which this study considers. Observations from either experimental data, or surrogate data from a numerical method, are required for the training of machine-learning models. In this study, a comprehensive training set for the machine learning was created from excess attenuation predictions made with a Crank-Nicholson parabolic equation (CNPE) model. Latin hypercube sampling of the parameter space (source frequency, meteorological factors, boundary conditions, and propagation geometries) generates a set of input for the CNPE model and machine-learning models. Consideration is given to ensemble decision trees, ensemble n...

Recent statistical analyses indicate that the large, seemingly random scatter in community noise annoyance survey data results from systematic variations in noise tolerance between communities. This paper describes a simple hierarchical (or multilevel) modeling approach to community noise, which incorporates variations in tolerance among individuals, communities, and surveys. A regression methodology consistent with this hierarchical perspective, namely, that of partial pooling with a generalized linear model, is also described and applied to survey data for transportation noise. From this approach, it is shown that the “community tolerance level” (CTL) model proposed by Fidell et al. [J. Acoust. Soc. Am. 130, 791–806 (2011)] is a particular case of partial pooling regression, in which it is implied that the annoyance responses of all surveyed communities are independent and grow at a fixed rate with increasing day-night level. Simulations and a meta-analysis of transportation noise annoyance studies prov...