Edward T. Nykaza

Information-criterion based selection of models for community noise annoyancea)

Statistical evidence for various models relating day-night sound level (DNL) to community noise annoyance is assessed with the Akaike information criterion. In particular, community-specific adjustments such as the community tolerance level (CTL, the DNL at which 50% of survey respondents are highly annoyed) and community tolerance spread (CTS, the difference between the DNL at which 90% and 10% are highly annoyed) are considered. The results strongly support models characterizing annoyance on a community-by-community basis, rather than with complete pooling and analysis of all available surveys. The most likely model was found to be a 2-parameter logistic model, with CTL and CTS fit independently to survey data from each community.

Minimizing sleep disturbance from blast noise producing training activities for residents living near a military installation

Field research was conducted during 2004 in the vicinity of a United States military installation to determine if awakening of residents due to blast noise from large military weapons might vary during the night. Analysis of the data indicates that awakening from blast noise is significantly less likely during the time period between midnight and 0200 h compared to time periods before midnight and approaching dawn. These findings suggest that postponing noisy evening training until after midnight could effectively reduce the negative impact of nighttime training on local residents and thus help to preserve nighttime training capabilities.

On the relationship between blast noise complaints and community annoyance.

Military installations typically rely on noise complaints to indicate adverse noise environments and often restrict the firing of certain weapons to reduce the number of noise complaints. Using complaints in this manner may also imply that the absence of complaints is an indicator of low community annoyance. The relationship between individual complaints and general community annoyance, however, is currently not established, and it is unknown whether implementing restrictions in reaction to individual complaints is an appropriate or necessary way to reduce community annoyance. This paper looks at whether there are significant differences in reported annoyance to complaint-referenced blast events and general military noise annoyance between those who complain and their non-complaining neighbors. Those who complained were significantly more annoyed to both complaint-referenced blast events and general military noise in comparison to their non-complaining neighbors. The implications of these findings are discussed in terms of range management.

Blast noise characteristics as a function of distance for temperate and desert climates

Variability in received sound levels were investigated at distances ranging from 4 m to 16 km from a typical blast source in two locations with different climates and terrain. Four experiments were conducted, two in a temperate climate with a hilly terrain and two in a desert climate with a flat terrain, under a variety of meteorological conditions. Sound levels were recorded in three different directions around the source during the summer and winter seasons in each location. Testing occurred over the course of several days for each experiment during all 24 h of the day, and meteorological data were gathered throughout each experiment. The peak levels (L(Pk)), C-weighted sound exposure levels (CSEL), and spectral characteristics of the received sound pressure levels were analyzed. The results show high variability in L(Pk) and CSEL at distances beyond 2 km from the source for each experiment, which was not clearly explained by the time of day the blasts occurred. Also, as expected, higher frequency energy is attenuated more drastically than the lower frequency energy as the distance from the source increases. These data serve as a reference for long-distance blast sound propagation.

Comparisons between physics-based, engineering, and statistical learning models for outdoor sound propagation.

Many outdoor sound propagation models exist, ranging from highly complex physics-based simulations to simplified engineering calculations, and more recently, highly flexible statistical learning methods. Several engineering and statistical learning models are evaluated by using a particular physics-based model, namely, a Crank-Nicholson parabolic equation (CNPE), as a benchmark. Narrowband transmission loss values predicted with the CNPE, based upon a simulated data set of meteorological, boundary, and source conditions, act as simulated observations. In the simulated data set sound propagation conditions span from downward refracting to upward refracting, for acoustically hard and soft boundaries, and low frequencies. Engineering models used in the comparisons include the ISO 9613-2 method, Harmonoise, and Nord2000 propagation models. Statistical learning methods used in the comparisons include bagged decision tree regression, random forest regression, boosting regression, and artificial neural network models. Computed skill scores are relative to sound propagation in a homogeneous atmosphere over a rigid ground. Overall skill scores for the engineering noise models are 0.6%, -7.1%, and 83.8% for the ISO 9613-2, Harmonoise, and Nord2000 models, respectively. Overall skill scores for the statistical learning models are 99.5%, 99.5%, 99.6%, and 99.6% for bagged decision tree, random forest, boosting, and artificial neural network regression models, respectively.

Blast noise classification with common sound level meter metrics

A common set of signal features measurable by a basic sound level meter are analyzed, and the quality of information carried in subsets of these features are examined for their ability to discriminate military blast and non-blast sounds. The analysis is based on over 120 000 human classified signals compiled from seven different datasets. The study implements linear and Gaussian radial basis function (RBF) support vector machines (SVM) to classify blast sounds. Using the orthogonal centroid dimension reduction technique, intuition is developed about the distribution of blast and non-blast feature vectors in high dimensional space. Recursive feature elimination (SVM-RFE) is then used to eliminate features containing redundant information and rank features according to their ability to separate blasts from non-blasts. Finally, the accuracy of the linear and RBF SVM classifiers is listed for each of the experiments in the dataset, and the weights are given for the linear SVM classifier.

Use of actimeters to determine awakenings by sounds of large guns

The U.S. Army has been using the day-night average sound level (DNL) to manage the community noise impact from heavy weapons noise since the late 1970s. In this case, the DNL is C-weighted as recommended by the National Academy of Sciences-National Research Council Committee on Hearing, Bioacoustics and Biomechanics (CHABA). CHABAs recommendation was justified by the fact that C-weighting (originally developed for the loudness of intense sounds) measures lower frequency sound energy in large guns which is otherwise missed by A-weighting. When the CHABA methodology was first adopted, there was relatively little night firing, but, today, night vision technology makes firing during darkness an absolute necessity for military readiness. Recognizing that the 10-dB penalty incorporated in the DNL methodology was not intended to predict sleep disturbance and that sleep disturbance may be a function of discrete noise event levels rather than annual-average noise levels, the U.S. Army Engineer Research and Development Center initiated a project to measure sleep disturbance among people living near tank gunnery ranges. A first step in this project was to evaluate whether a commonly-used instrument for measuring sleep disturbance, the actimeter, would be sensitive to awakenings from blast noise. After preliminary screening of three designs of actimeter, the preferred design was tested in cooperation with the Army Center for Health Promotion and Preventive Medicine with subjects sleeping inside the Army Research Laboratorys Hostile Environment Simulator. Subjects were exposed to nighttime blasts at two linear peak sound pressure levels (110 dB and 120 dB). The results confirmed that the preferred design would be a reliable and rugged instrument for the actual field study of awakening from live fire. This article is a government work and as such, is in the public domain and not subject to copyright.

Community response to blast noise

Although community response to impulsive noise from military operations is usually discussed for NEPA‐related purposes in terms of the prevalence of annoyance, it is managed on a local, daily basis in terms of numbers of recent complaints. Reconciling blast noise complaint rates with the annoyance predicted by dosage‐effect analysis would be of considerable benefit to the Army, since it would provide insight into the dynamics of community reaction to this distinctive form of noise exposure, and put its assessment and management on a common footing. This paper describes a systematic approach to the challenges of quantifying community reaction to blast noise. [Work supported by ERDC‐CERL.]

Impact of Parametric Uncertainties on Scattered Signal Distributions and Receiver Operating Characteristics

Many different distributions are used to model statistics of waves that have been randomly scattered in atmospheric and terrain environments. These distributions have varying analytical advantages and ranges of physical applicability. This report reviews several basic distributions and discusses how they can be extended to include spatial and temporal variability in the scattering process. For this purpose, a compound probability density function (pdf) can be introduced in which a basic pdf describing the underlying scattering process is modulated by a second pdf describing parametric uncertainties in the scattering. We describe some useful new formulations based on the compound pdf, including strong and Rytov (lognormal) scattering processes modulated by the environment. These new formulations lead to relatively simple marginalized signal power distributions (Lomax and lognormal, respectively). Furthermore, we show how the conditional scattered signal pdf may be viewed as a likelihood function in which the modulating pdf is the Bayesian conjugate prior. The parameters of the modulating process can thus be refined by simple sequential Bayesian updating. Finally, the impact of the parametric uncertainties on signal detection and receiver operating characteristic curves is discussed and shown to be a very important consideration in practical applications. DISCLAIMER: The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED. DO NOT RETURN IT TO THE ORIGINATOR.

High energy large scale blast sound propagation experiments

Atmospheric conditions greatly affect the propagation of the sound. Currently, little information exists regarding the amount of variation in level and spectra of blast noise that is caused by changing meteorological conditions along the propagation path. Available meteorological models accurately predict vertical sound speed profiles only up to the top of the boundary layer. For long-range propagation, this is inadequate. Vertical sound speed profile data and resulting propagation effects will help to better explain the effects of atmospheric refraction in sound propagation. This report detailed the procedures and equipment used to carry out a series of blast noise experiments at White Sands Missile Range, NM and Fort Leonard Wood, MO from 2007 to 2009. The data provided by this large-scale experiment comprise a definitive dataset for the effects of a wide range of meteorological conditions on long-range high-energy blast sound propagation in climate types similar to the majority of continental United States (CONUS) military installations (arid desert and temperate vegetated). The experiment also captured a comprehensive set of meteorological measurements over the duration of the experiments. DISCLAIMER: The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED. DO NOT RETURN IT TO THE ORIGINATOR.