Introduction to Sound Propagation Under Water

This article presents a method for performing noise constrained optimization of wind farms by changing the operational modes of the individual wind turbines. The optimization is performed by use of the TopFarm framework and the PyWake wind farm modeling as well as two sound propagation models: the ISO 9613-2 model and the Parabolic Equation model, WindSTAR. The two sound propagation models introduce different levels of complexity to the optimization problem with the WindSTAR model taking a broader range of parameters, like the acoustic ground impedance, the complex terrain elevation and the flow field from the noise source to the receptor, into account. Thus, as the WindSTAR model introduces a higher complexity of the sound propagation computations, it likewise introduces a higher computational time. Wind farm optimization using each of the two sound propagation models is therefore performed in different atmospheric conditions and for different source/receptor setups, and compared through this study in order to evaluate the advantage of using a more complex sound propagation model. The article focuses on artificial wind farms in flat terrain as well as arbitrarily chosen dwellings at which the noise constraints are applied. By this, the study presents the potential of an optimization algorithm focusing on the sound propagation and wind farm operation trade-off.

This paper deals with the sound propagation modeling in urban area. This problematic requires to take into account many phenomena that can have a substantial impact as well in semienclosed spaces as on long-range outdoor sound propagation, such as reflections and absorption on the frontages and on the ground, atmospheric attenuation, sound velocity variations related with wind and temperature vertical gradients, atmospheric turbulences. The numerical method used is the TLM (transmission line modeling), which has been originated in electromagnetism and adapted for acoustics applications. It consists in a physical rendering of the waves propagation based on the Huygens' principle. It is established on a spatiotemporal discretization of the domain using an iterative temporal process for sound pressure propagation, instead of the resolution of mathematical equations. The TLM model has then been developed in two and three dimensions allowing to combine all the phenomena affecting the sound propagation in urban area. Numerical simulations are given for canyon streets.

Sound propagation of wind farms is typically simulated by the use of engineering tools that are neglecting some atmospheric conditions and terrain effects. Wind and temperature profiles, however, can affect the propagation of sound and thus the perceived sound in the far field. A better understanding and application of those effects would allow a more optimized farm operation towards meeting noise regulations and optimizing energy yield. This paper presents the parabolic equation (PE) model development for accurate wind turbine noise propagation. The model is validated against analytic solutions for a uniform sound speed profile, benchmark problems for nonuniform sound speed profiles, and field sound test data for real environmental acoustics. It is shown that PE provides good agreement with the measured data, except upwind propagation cases in which turbulence scattering is important. Finally, the PE model uses computational fluid dynamics results as input to accurately predict sound propagation for complex flows such as wake flows. It is demonstrated that wake flows significantly modify the sound propagation characteristics.

This finite-difference time domain (FDTD) model for sound propagation in very shallow water uses pressure and velocity grids with both 3-dimensional Cartesian and 2-dimensional cylindrical implementations. Parameters, including water and sediment properties, can vary in each dimension. Steady-state and transient signals from discrete and distributed sources, such as the surface of a vibrating pile, can be used. The cylindrical implementation uses less computation but requires axial symmetry. The Cartesian implementation allows asymmetry. FDTD calculations compare well with those of a split-step parabolic equation. Applications include modeling the propagation of individual fish sounds, fish aggregation sounds, and distributed sources.

The seabed possesses variations in its material properties, layering structure, slope and roughness making prediction, and analysis of sound propagation in shallow water highly complex. For certain frequency ranges, the effect of roughness becomes significant. Numerous models have been adopted to account for the scattering of acoustic waves by rough surfaces, including Kirchhoff approximation (for relatively large scales of roughness), small perturbation theory (for relatively small scales of roughness), and small slope approximation, which bridges across the two regimes under certain conditions. Although grounded in analytical theory, these approaches invariably involve the computation of numerical integrals so additional approximation theories have been explored including stationary phase methods and Taylor series approximations. In this study, these semi-analytical methods are incorporated within a new sound propagation model and compared with a numerical graphics processing unit (GPU)-accelerated finite element model incorporating roughness parameters (root mean square height and correlation length) for rough, sloped seabed geometries (with gradients ranging from 0° to 45°) in shallow water environments. The effect of large- and small-scale roughness on sound propagation is investigated in two- and three-dimensional space. The finite element modelling is used to validate the optimal choice of semi-analytical method for the different environments considered.

The objectives of this paper are to analyze the effectiveness of parameters on sound propagation in a shallow-water environment. The procedure for calculation of transmission loss is only the method to analyze the influence of environmental parameters. The normal mode approach is carried out for the calculation of transmission loss. And it is conducted in the range independent environment Transmission loss for sound propagation in shallow water depends upon many natural variables such as sea surface, water medium, and sea bottom. Analyses are finalized on the results obtained by considering two types of sound channels. The results indicated that acoustic transmission loss in a shallow-water environment is dependent on the source & receiver depths, sea surface, sound speed profile (SSP) in water, sound speed in bottom, density of water & bottom, propagation range and frequency. It is necessary to mention that better transmission was found during the sound velocity increases with depth; whereas the poor transmission occurred in negative gradient channel.

Sound propagation models have typically been used to develop noise control solutions for a wide variety of troublesome sources from highways, power plants, and airports to stadiums and outdoor amphitheaters. Almost all of these models assume that there is no variability in the atmospheric properties of the propagating medium but this assumption is almost invariably false. Predictions from these models are usually validated during the day when propagation conditions are favorable, producing lower levels than the models calculate. The problems usually come at night, when temperature and wind variations in the atmosphere create propagation conditions which are not favorable, resulting in much higher noise levels in the community, often on the order of 15–20 dB. This paper describes work which has been undertaken by the Walt Disney Company in an effort to produce a more precise computer model for these unfavorable conditions. The model developed is based on Gaussian beams, a hybrid technique developed to retain some of the fundamental aspects of ray tracing while incorporating some of the more advanced GFPE concepts. The fundamental code, developed by Ken Gilbert and Xiao Di, is being integrated into SOUNDPLAN, a commercially available sound propagation computer program.

A model of ambient noise is described which permits one to estimate the density of whitecaps at the sea surface as well as the scaling as a function of wind speed of whitecap coverage and characteristic surface. This model relates the statistical properties of underwater sound (first and second moments) to whitecap distribution at the sea surface and to underwater sound propagation. The sound propagation model accounts for seabed reflections. Simulations show that seabed reflection effects can be great in shallow water, implying that the listening radii for hydrophone measurements, as defined by Farmer and Vagle (1988), can often be very large compared to hydrophone depth.

For applications of porous materials where mean pressure drop is a concern, packaging the material into a corrugated structure is better compared to other geometries such as block or wedge shapes. The goal of this study is to integrate noise reduction functionality within that material, which requires an understanding of sound propagation through corrugated porous structures, including flow effects. The corrugated porous structure involves porous partitions separating inlet and outlet fluid channels. The porous materials considered are periodic octet-truss and body-centered cubic unit cells, and sound propagation across these porous partitions is modeled using the Johnson–Champoux–Allard model. The predicted transmission loss (TL) is benchmarked using designed additively manufactured corrugated structures measured using a flow duct. The laminar flow regime is maintained across the porous structure to reduce flow-noise effects. It is shown that the TL for a given corrugated structure increases with a decrease in porosity, and the impact of flow becomes significant as the porosity decreases. The influence of flow on TL also depends on the unit cell configuration. Furthermore, the model provides insights into pressure and acoustic particle velocity distributions within the corrugated structure and reveals regions of the porous material that effectively participate in noise reduction.

A tank experiment is being conducted to explore sound propagation in a continuously stratified ocean containing internal gravity waves that produce fluctuations in acoustic signals. The tank is filled with water of increasing salinity with increasing depth in the fluid; the variation in salinity results in a 150 m/s variation of the sound speed over the 50 cm-depth fluid. Sound arrival times determined in three-dimensional hydrophone scans map out the sound diffraction pattern in the stratified fluid. Good agreement is found between the measurements and results obtained from wavefront modeling by ray acoustics. Sound fluctuations produced by internal waves are measured for several acoustic track locations and at different phases of the internal waves that radiate from a mechanical wave generator. Internal wave fields measured by particle image velocimetry provide input for a parabolic equation model, which is used to predict the sound fluctuations for comparison with measurements. This research is designed to improve the understanding and modeling of sound propagation and scattering by internal waves in the realistic oceans. [Research support: The 2013-14 ASA F. V. Hunt Postdoctoral Research Fellowship (L. Zhang) and ONR MURI Grant N000141110701 (WHOI).]

Energy usage is on the rise in both Canada and the United States. Because of this, there is a growing demand and strain on the current infrastructure. More importantly though, there is a strong demand for the use of renewable energy sources to meet this demand. One of the most popular renewable energy sources at this time is the wind turbine. In Ontario, there are plans to implement a significant number of them throughout the province. There are concerns though from residents in the vicinity of them that they cause too much noise, as well as health issues. However, some argue that these complaints stem from incorrectly calculated setback distances due to the lack of use of a detailed sound propagation model. In this study, a sound propagation model was developed using a Finite-Difference Time-Domain method, for a three dimensional computational domain, and simulated using data for a Siemens SWT-2.3-101 wind turbine. The simulations produced data of the sound propagation characteristics of each emitted wave, for each tested case. The model was developed as a starting point and building block for the eventual use in simulations of large domains and complex flow phenomena.

The primary focus of the work was to estimate propagation loss and provide a quantitative estimate in transmission loss using sound propagation modeling in shallow waters of south west Bay of Bengal and also to validate the results with field measurements. KRAKEN normal mode sound propagation for a range independent environment in the frequency range of 850-1050 Hz was used for the simulation. The water depth was taken as 20 m. Transmission loss is estimated at four different ranges for a source at 10 m depth by using the essential acoustic input parameters. To validate results obtained through modeling, an experiment was conducted to measure transmission loss directly in an environment that closely matched with the model. The results of transmission loss estimated using the model was compared with the field measurements at short ranges.

An undulating bottom in shallow water has a significant effect on sound propagation. An acoustic propagation experiment was carried out in the East China Sea in 2020. Measurements along two separate propagation tracks with flat and undulating bottoms were obtained. Abnormal transmission losses (TLs) were observed along the track with the undulating bottom. By using the parabolic equation model RAM and ray theory, these abnormal TLs and the distribution of the sound field energy were analyzed. Numerical simulations indicate that under the shallow water condition with a negative thermocline and for a high frequency (1000 Hz), the incidence and reflection angles of sound rays on the sea bottom are changed due to the undulating sea bottom. The larger the inclination angle of the undulating bottom, the greater the grazing angle changes. These angles changes lead to different sound propagation paths for the undulating bottom and the flat bottom, resulting in the difference of TLs at a certain distance and depth. The undulating bottom will cause energy convergence in the mixed layer when the source and receiver locate above the thermocline.

Despite of small land area, Japan has vast EEZ, which is expected to have potential mineral resources. Extensive seismic surveys have been conducted for those targets. However, airguns used for the survey generate intense and low-frequency impulse sound, which could disturb or harm marine mammal behavior and auditory system. In June 2016, NOAA released “Ocean Noise Strategy Roadmap” that recommends modeling of sound propagation in the context of realistic environmental parameters to assess noise impacts on marine creatures. Japan has remarkable seasonal climate changes and complex ocean-bottom topography with trenches and seamounts; therefore, such model is worthwhile. Here, we propose a modeling method utilizing ARGO data includes seasonal climate changes and LEVITUS data, and ocean-bottom topographic configuration data from Google Earth. We calculated long range propagation of airgun sounds in different sound profiles and ocean-bottom topographic configurations around Ogasawara Islands, which is known as a cetacean habitat. Results showed that seasonal climate change and the precision of the ocean-bottom topographic configuration caused significant differences in sound propagation. These findings suggest that the realistic environmental parameters is essentially needed for the modeling of sound propagation and proposed method is a useful tool to assess noise impacts on marine mammals.

The connection between Titan's atmosphere and its surface is unique: it is at the origin of a variety of surface processes, in particular of surface-atmosphere interactions – liquid methane flows, waves, rainfall, dune movements, saltation, dust devils, and rainstorms, etc.- all play an important role in surface alteration and atmospheric dynamics. Interestingly, Titan's atmosphere is dense enough to propagate the acoustic waves generated by these phenomena. Therefore, they can be studied quantitatively and remotely by recording their acoustic signatures. In the mid-2030s, the Dragonfly mission will explore Titan near an equatorial impact crater with a relocatable rotorcraft lander. Key geophysical and meteorological measurements will be provided by the DraGMet package, a suite of 12 experiments, including three microphones.In preparation for this acoustic exploration, modeling of sound propagation under Titan's atmospheric conditions is a prerequisite for assessing the levels and detection ranges of geophysical sound sources for the DraGMet microphone. As a first step in this modeling, acoustic attenuation calculations showed that Titan's unique N2-CH4 atmosphere at ~90 K can sustain acoustic waves over long distances due to relatively low absorption compared to Earth. In addition, tracking sound velocity and acoustic attenuation on Titan could help constrain the minor component fraction in the atmosphere. In this presentation we report on the second step of the modeling, which consists of a parabolic equation solver that computes the sound field produced by a sound source for given atmospheric parameters (wind and temperature profiles, ground properties, see Fig. 1). Booming sand, a possible sound source at the Dragonfly landing site, is propagated into the model to assess the maximum distance at which such an event could be recorded.Fig. 1. Sound pressure level distribution for the propagation of a 250 Hz sound source located at 35m from a perfectly reflecting ground. (Top) Terrestrial atmosphere at 293 K and with a constant wind speed of 2 m/s. (Bottom) Titan atmosphere at 90 K and with a constant wind speed of 0.5 m/s. Sound propagates in the upwind direction.