Search

As awareness on the impact of anthropogenic underwater noise on marine life grows, underwater noise measurement programs are needed to determine the current status of marine areas and monitor long-term trends. The Joint Monitoring Programme for Ambient Noise in the North Sea (JOMOPANS) collaborative project was funded by the EU Interreg to collect a unique dataset of underwater noise levels at 19 sites across the North Sea, spanning many different countries and covering the period from 2019 to 2020. The ambient noise from this dataset has been characterised and compared - setting a benchmark for future measurements in the North Sea area. By identifying clusters with similar sound characteristics in three broadband frequency bands (25-160 Hz, 0.2-1.6 kHz, and 2-10 kHz), geographical areas that are similarly affected by sound have been identified. The measured underwater sound levels show a persistent and spatially uniform correlation with wind speed at high frequencies (above 1 kHz) and a correlation with the distance from ships at mid and high frequencies (between 40 Hz and 4 kHz). Correlation with ocean current velocity at low frequencies (up to 200 Hz), which are susceptible to nonacoustic contamination by flow noise, was also evaluated. These correlations were evaluated and simplified linear scaling laws for wind and current speeds were derived. The presented dataset provides a baseline for underwater noise measurements in the North Sea and shows that spatial variability of the dominant sound sources must be considered to predict the impact of noise reduction measures., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Fritjof Basan reports financial support was provided by North Sea Region of the European Regional Development Fund (InterReg) of the European Union., (Crown Copyright © 2023. Published by Elsevier Ltd. All rights reserved.)

A proposal is described for an underwater sensor combining an acoustic device with an optical one to automatically size juvenile bluefin tuna from a ventral perspective. Acoustic and optical information is acquired when the tuna are swimming freely and the fish cross our combined sensor's field of view. Image processing techniques are used to identify and classify fish traces in acoustic data (echogram), while the video frames are processed by fitting a deformable model of the fishes' ventral silhouette. Finally, the fish are sized combining the processed acoustic and optical data, once the correspondence between the two kinds of data is verified. The proposed system is able to automatically give accurate measurements of the tuna's Snout-Fork Length (SFL) and width. In comparison with our previously validated automatic sizing procedure with stereoscopic vision, this proposal improves the samples per hour of computing time by 7.2 times in a tank with 77 juveniles of Atlantic bluefin tuna ( Thunnus thynnus ), without compromising the accuracy of the measurements. This work validates the procedure for combining acoustic and optical data for fish sizing and is the first step towards an embedded sensor, whose electronics and processing capabilities should be optimized to be autonomous in terms of the power supply and to enable real-time processing.

Active acoustic sensors are widely used in oceanographic and environmental studies. Although many have nominal operating frequencies above the range of marine mammal hearing, they can produce out-of-band sound that may be audible to marine mammals. Acoustic emissions from four active acoustic transducers were characterized and compared to marine mammal hearing thresholds. All four transducers had nominal operating frequencies above the reported upper limit of marine mammal hearing, but produced measurable sound below 160 kHz. A spatial map of the acoustic emissions of each sonar is used to evaluate potential effects on marine mammal hearing when the transducer is continuously operated from a stationary platform. Based on the cumulative sound exposure level metric, the acoustic emissions from the transducers are unlikely to cause temporary threshold shifts in marine mammals, but could affect animal behavior. The extent of audibility is estimated to be, at most, on the order of 100 m., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The top predators in coastal marine ecosystems, such as whales, dolphins, seabirds, and large predatory fishes (including sharks), may compete with each other to exploit food aggregations. Finding these patchy food sources and being first to a food patch could provide a significant competitive advantage. Our hypothesis is that food patches have specific sound signatures that marine predators could detect and that acoustic sources and animal sensory capabilities may contribute to competition dynamics. Preliminary analysis shows that diving gannets have a distinct spectral signature between 80 and 200 Hz, which falls within the hearing sensitivity of large pelagic fishes. Therefore, we suggest that diving birds may contribute to the sound signatures of food aggregations, linking competition dynamics both above and below the water surface.

To monitor the underwater sound and pressure waves generated by anthropogenic activities such as underwater blasting and pile driving, an autonomous system was designed to record underwater acoustic signals. The underwater sound recording device (USR) allows for connections of two hydrophones or other dynamic pressure sensors, filters high frequency noise out of the collected signals, has a gain that can be independently set for each sensor, and allows for 2 h of data collection. Two versions of the USR were created: a submersible model deployable to a maximum depth of 300 m, and a watertight but not fully submersible model. Tests were performed on the USR in the laboratory using a data acquisition system to send single-frequency sinusoidal voltages directly to each component. These tests verified that the device operates as designed and performs as well as larger commercially available data acquisition systems, which are not suited for field use. On average, the designed gain values differed from the actual measured gain values by about 0.35 dB. A prototype of the device was used in a case study to measure blast pressures while investigating the effect of underwater rock blasting on juvenile Chinook salmon and rainbow trout. In the case study, maximum positive pressure from the blast was found to be significantly correlated with frequency of injury for individual fish. The case study also demonstrated that the device withstood operation in harsh environments, making it a valuable tool for collecting field measurements.

Sound exposure studies require replicated sound treatments for the results to be representative for sound classes in general. Additionally, reused treatments in replicated designs need to be accounted for statistically. The lack hereof is referred to as simple and sacrificial pseudoreplication, respectively, and results should be interpreted accordingly. We quantified the occurrence of these issues and subsequent interpretation of results in 104 underwater sound exposure studies (2019–2023). The majority of the studies (85%) did not replicate sound treatments. From the ones that did, most did not statistically acknowledge the hierarchical structure of the data. Unreplicated treatment designs limit the generalizability of the findings. Nevertheless, only small differences were found in how the results of unreplicated and replicated treatment designs were interpreted. This commentary aims to provide guidance in the design, analysis and interpretation of sound exposure studies, which are equally valid for aquatic and terrestrial research. • We quantified sound treatment pseudoreplication in underwater sound exposure studies. • Most papers did not replicate sound treatments (simple pseudoreplication). • Hierarchical treatment designs were often not statistically acknowledged. • We hope to contribute to reducing pseudoreplication in sound exposure studies. [ABSTRACT FROM AUTHOR]

In the shift toward sustainable energy production, offshore wind power has experienced notable expansion. Several projects to install floating offshore wind farms in European waters, ranging from a few to hundreds of turbines, are currently in the planning stage. The underwater operational sound generated by these floating turbines has the potential to affect marine ecosystems, although the extent of this impact remains underexplored. This study models the sound radiated by three planned floating wind farms in the Strait of Sicily (Italy), an area of significant interest for such developments. These wind farms vary in size (from 250 MW to 2800 MW) and environmental characteristics, including bathymetry and seabed substrates. Propagation losses were modeled in one-third-octave bands using JASCO Applied Sciences' Marine Operations Noise Model, which is based on the parabolic equation method, combined with the BELLHOP beam-tracing model. Two sound speed profiles, corresponding to winter and summer, were applied to simulate seasonal variations in sound propagation. Additionally, sound from an offshore supply ship was incorporated with one of these wind farms to simulate maintenance operations. Results indicate that sound from operating wind farms could reach a broadband sound pressure level (Lp) of 100 dB re 1 µPa as far as 67 km from the wind farm. Nevertheless, this sound level is generally lower than the ambient sound in areas with intense shipping traffic. The findings are discussed in relation to local background sound levels and current guidelines and regulations. The implications for environmental management include the need for comprehensive monitoring and mitigation strategies to protect marine ecosystems from potential acoustic disturbances. [ABSTRACT FROM AUTHOR]

The rarest seal and the world's most endangered pinniped species, the Mediterranean monk seal (Monachus monachus), has a small and isolated population in the Madeira Archipelago (Portugal). This species tends to be extremely wary of humans and, therefore, very difficult to approach and study.Passive acoustic monitoring (PAM) is a non‐invasive, cost‐effective tool that can be a valuable complement for the traditional monitoring methods, providing insight for effective conservation of the seal in the Madeira Archipelago.In this pilot study, custom‐designed autonomous underwater recorders were deployed in two marine protected areas (Garajau Partial Nature Reserve and the Desertas Islands Nature Reserve) to assess the potential of PAM to detect and monitor this elusive and endangered species in the Madeira Archipelago.Two call types putatively produced by M. monachus were detected in a subsample of audio files recorded over a 3‐month acoustic deployment; these call types share similarities with the /growl/ and /hiccup/ recently described for M. monachus in a Mediterranean population. The most common sound type detected was the low‐frequency growl. No obvious pattern was found in the abundance of sounds according to sampling date, and no significant difference was found in the abundance of sounds in different periods of the day.The ability to detect the species' underwater vocalizations with PAM opens the possibility of future monitoring plans based on data obtained from audio recordings. These data can provide relevant information for conservation, namely, on the presence and abundance of the seals. [ABSTRACT FROM AUTHOR]

Fish species and aquatic invertebrates are sensitive to underwater sound particle motion. Studies on the impact of sound on marine life would benefit from sound particle motion models. Benchmark cases and solutions are proposed for the selection and verification of appropriate models. These include a range-independent environment, with and without shear in the sediment, and a range-dependent environment, without sediment shear. Analysis of the acoustic impedance illustrates that sound particle velocity can be directly estimated from the sound pressure field in shallow water scenarios, except at distances within one wavelength of the source, or a few water depths at frequencies where the wavelength exceeds the water depth. [ABSTRACT FROM AUTHOR]

• A theoretical method is developed to get the sound absorption performance of the FG coating excited by a phased array. • 2. FFT parameters in the angular spectrum method is discussed in detail. • 3. Parametric analyses give some new phenomena and meaningful conclusions. • 4. The angular spectrum decomposition of the incident sound field is utilized for mechanism analysis. Laying anechoic coatings on the surface of underwater vehicles is an effective technology to improve the acoustic stealth performance. Meanwhile, the detection waves may have complex directivity, and it is important to study their influence on the sound absorption of the coating. This article introduces a functionally graded coating under a phased arc array incidence, which simulates a novel anechoic coating on an underwater vehicle to absorb sound waves emitted by active sonars. The incident field of the phased array is constructed by spherical harmonic expansion and the superposition principle. The wave propagation of the functionally graded coating is analyzed through an equivalent laminated model and the reverberation matrix method. Utilizing the angular spectrum method, the reflected sound field and absorption coefficient of the coating under the phased arc array incidence are predicted and the theoretical method is formed. Then the selections of parameters in Fourier transforms of the angular spectrum method are discussed for achieving converged results. A finite element analysis is applied to verify the effectiveness and calculation speed of the proposed method through the establishment of detailed quarter or half model. The effect of phased arc array parameters and the coating on the absorption and reflection performances are further studied. The angular spectrum decomposition of the incident sound field explains the changing trends of the sound absorption curves. The present work provides an important way to deal with this complex underwater sound propagation problem. [ABSTRACT FROM AUTHOR]

Passive acoustic monitoring of the global ocean has increased dramatically over the last decade, providing insights into seasonal sea ice and wind/wave variability, biodiversity, geophysical hazards, and anthropogenic noise impacts. All of these phenomena are sentinels of marine ecosystem health and ocean climate change. Recognizing the utility of underwater sound, the Pacific Marine Environmental Laboratory (PMEL) formed a passive acoustic research program with the goal of quantifying deep-ocean and coastal soundscapes in support of NOAA's mission to conserve and manage marine ecosystems. PMEL Acoustics Program researchers have built a stable of novel ocean technologies, including autonomous stationary hydrophones, mobile platforms, and near-real-time surface buoys with satellite communication capability. These passive acoustic monitoring systems have been deployed in every major ocean basin on Earth, enabling significant advancements in understanding of natural and anthropogenic sounds. This progress includes evaluation of human-made sound levels across US waters, observations of ship noise fluctuations during the COVID-19 pandemic, and evaluation of noise levels from offshore wave-energy devices. Progress in natural sound research includes assessment of seasonal variability in the presence of endangered cetacean species due to population recovery and/or changing ocean temperatures as well as early detection of the collapse of an Antarctic ice shelf. [ABSTRACT FROM AUTHOR]

High-speed video filming of surface currents and synchronized acoustic measurements of the underwater sound signals of falling drops were performed in a laboratory tank. During successive falling, the main structural elements of collision of a single drop with the surface are preserved in distorted form in the flow pattern: cavity, splashes, crown, and splash; shock pulses accompanying each contact are stably repeated in the phonogram. In addition, rare resonance packets are observed. For multiple falling drops, the flow pattern changes dramatically: the main structural elements of the drop impact flow disappear, and the surface is covered with floating bubbles. The phonogram assumes the form of a noise signal, in the spectrum of which separate linear sections stand out. [ABSTRACT FROM AUTHOR]

Bottom formations known as pockmarks basically arise due to extensive gas emission. Active pockmarks are characterized by exceptionally high gas saturation and substantially reduced sound speed. The latter circumstance leads to strong attenuation of sound waves contacting with a pockmark. In the present paper, we study low-frequency sound propagation in a 10-km long waveguide crossing a giant pockmark. A new method of acoustic waveguide scanning based on measurement of the wavefield propagator is represented. This method allows one to explore attenuation anomalies associated with the presence of the gas-saturated bottom region. In particular, one can find out which beams fall into a pockmark area and therefore experience strong losses. Identifying such beams, as well as beams which avoid pockmark-assisted losses, one can estimate probable locations of the pockmark segment in the waveguide, provided information about the background medium is sufficient. [ABSTRACT FROM AUTHOR]

Automated target recognition is an important task in the littoral warfare domain, as distinguishing mundane objects from mines can be a matter of life and death. This is initial work towards the application of convolutional autoencoding to the littoral sonar space, with goals of disentangling the reflection noise prevalent in underwater acoustics and allowing recognition of the shape and material of targets. The autoencoders were trained on magnitude Fourier transforms of the TREX13 dataset. Clusters in the encoding space representing the known variable of measurement distance between the target and the sensor were found. An encoding vector space of around 16 dimensions appeared sufficient, and the space was shown to generalize well to unseen data. [ABSTRACT FROM AUTHOR]

A prediction model of the sound velocity and sound attenuation of underwater cobalt-rich crusts (CRCs) was established to solve the problem that it is difficult to predict the sound velocity in thickness measurements of cobalt-rich crusts. Based on Biot theory and BISQ theory, a simplified Biot and BISQ model was proposed for the prediction of the sound velocity and sound attenuation of CRCs by using the Kozeny–Carman (KC) equation. The models could calculate the sound velocity and attenuation by the porosity and detection frequency. Based on the physical and mechanical properties of CRCs, a similarity model of the sound velocity and sound attenuation of CRCs was made by using the similarity theory to solve the problem that it is difficult to measure the acoustic propagation characteristics of CRCs. The sound velocity and sound attenuation of CRC similarity models with different porosities were measured by an underwater transmission experiment and the results of the simplified model calculation and experimental measurements were compared. The results showed that the simplified Biot model was suitable for the CRC sound velocity prediction and the simplified BISQ model was suitable for the CRC sound attenuation prediction, which had a high prediction accuracy. [ABSTRACT FROM AUTHOR]

In this brief we present a design of a full-duplex (FD) underwater acoustic communication (UAC) receiver with a two-sensor transducer. The transducer consists of two piezo-ceramic cylinders cast together in polyurethane resin; one acts as a hydrophone and the other a projector. As the distance between the projector and hydrophone is extremely short, a high level of self-interference (SI) from the projector is received at the hydrophone. This SI must be eliminated to enable far-end data demodulation. In this brief, we adopt a digital SI cancellation scheme based on adaptive filtering. We investigate the SI cancellation and far-end data demodulation performance with the two-sensor transducer in tank and lake experiments. The Rake receiver is used for the far-end data demodulation. As demonstrated by the experimental results, the far-end SNR loss in the FD experiment is less than 3 dB compared to the half-duplex experiment when there is only far-end transmission. [ABSTRACT FROM AUTHOR]

A closer look into the history of maritime geomedia reveals a historical intermezzo in which navigation in cases of unstable sight was realized with "Submarine Signaling" (SS). This infrastructure for the purpose of safe wayfinding along coasts operated from around 1900 to the early 1920s, relying upon submarine bells in the global oceans, and hydrophones and telephonic user interfaces in vessels. SS can be regarded as a starting point to the era of electrotechnological navigation, and is of media-historical interest insofar as its operability was based on undersea acoustics: shifting its epistemic focus from sight to sound, SS thus lay beyond the "visual regime" that characterizes our current digital geomedia cultures. Herein, I will reconstruct the genesis and history of SS, use it as a contrasting foil to our postmodern geomedia practices, and finally argue for an understanding of geomedia as historically variable phenomena. [ABSTRACT FROM AUTHOR]

Despite decades-long development, underwater communication systems still cannot achieve high data rates and long communication ranges at the same time (i.e., beyond 1 Mb/s and 1 km). Currently, acoustic communication is the only choice to achieve long distances. However, the inherent low acoustic bandwidth results in extremely low data rates. In this article, the acoustic reconfigurable intelligent surface (RIS) system is proposed to realize high-data-rate long-range underwater communications. Although the EM-based RIS has been widely investigated in terrestrial scenarios in recent years, the underwater acoustic RIS is based on completely different physics principles. Hence, the EM-based terrestrial RISs do not work for underwater acoustic signals. More-over, the long acoustic wave propagation delay, the inherent wideband nature, and the water behavior all impose unique challenges in underwater RIS operation. Therefore, this article presents a new hardware design to realize acoustic RIS, based on which the underwater RIS operation protocols are developed to address the aforementioned challenges. The proposed acoustic RIS system can be considered as an underwater infrastructure that enables beamforming functionalities for all types of devices, especially small robots and low-cost sensors. The simulation results show that the proposed acoustic RIS system can efficiently reflect acoustic waves and dramatically increase communication data rates and distances. [ABSTRACT FROM AUTHOR]

In this article an autonomous distributed-consensus system is evaluated with regard to its efficacy for establishing a common detection statistic among a network of passive acoustic hydrophones. The notion of consensus among sensors is briefly reviewed, and an algorithm motivated by diffusion of information among network neighbors is developed within the context of spectral graph theory. Relative entropy derived at each node provides information that the network averages to reach a joint detection decision. As the expected value of a log-likelihood ratio, relative entropy is the appropriate detection statistic for this application because it is nondimensional, additive, and insensitive to calibration. These properties facilitate the fusion of information among heterogeneous sensors. Seven nodes of an acoustical receiver network were moored on the New Jersey coastal shelf in May 2019, while towed and autonomous sources provided target signals at 900–1050 Hz. The convergence rate of the system to a detection statistic was found to be limited by slow acoustic communications, and convergence to a global consensus was often disrupted by communication breakdowns. When failures occurred, the network successfully demonstrated robustness by dissociating into viable subnetworks, each of which converged to a valid detection statistic. [ABSTRACT FROM AUTHOR]

The article presents an announcement of a conference Acoustics Week in Canada to be held from October 3-6, 2023, at Westin Hotels and Resorts in Montreal, Quebec.

Studies of the effects of sounds from underwater explosions on fishes have not included examination of potential effects on the ear. Caged Pacific mackerel (Scomber japonicus) located at seven distances (between approximately 35 and 800 m) from a single detonation of 4.5 kg of C4 explosives were exposed. After fish were recovered from the cages, the sensory epithelia of the saccular region of the inner ears were prepared and then examined microscopically. The number of hair cell (HC) ciliary bundles was counted at ten preselected 2500 μm2 regions. HCs were significantly reduced in fish exposed to the explosion as compared to the controls. The extent of these differences varied by saccular region, with damage greater in the rostral and caudal ends and minimal in the central region. The extent of effect also varied in animals at different distances from the explosion, with damage occurring in fish as far away as 400 m. While extrapolation to other species and other conditions (e.g., depth, explosive size, and distance) must be performed with extreme caution, the effects of explosive sounds should be considered when environmental impacts are estimated for marine projects. [ABSTRACT FROM AUTHOR]

Studies of the effects of sounds from underwater explosions on fishes have not included examination of potential effects on the ear. Caged Pacific mackerel (Scomber japonicus) located at seven distances (between approximately 35 and 800 m) from a single detonation of 4.5 kg of C4 explosives were exposed. After fish were recovered from the cages, the sensory epithelia of the saccular region of the inner ears were prepared and then examined microscopically. The number of hair cell (HC) ciliary bundles was counted at ten preselected 2500 μm2 regions. HCs were significantly reduced in fish exposed to the explosion as compared to the controls. The extent of these differences varied by saccular region, with damage greater in the rostral and caudal ends and minimal in the central region. The extent of effect also varied in animals at different distances from the explosion, with damage occurring in fish as far away as 400 m. While extrapolation to other species and other conditions (e.g., depth, explosive size, and distance) must be performed with extreme caution, the effects of explosive sounds should be considered when environmental impacts are estimated for marine projects. [ABSTRACT FROM AUTHOR]

The accurate detection and quantification of submerged targets has been recognized as a key challenge in marine exploration, one that traditional census approaches cannot handle efficiently. Here we present a deep learning approach to detect the pattern of a moving fish from the reflections of an active acoustic emitter. To allow for real-time detection, we use a convolutional neural network, which provides the simultaneous labeling of a large buffer of signal samples. This allows to capture the structure of the reflecting signal from the moving target and to separate it from clutter reflections. We evaluate system performance both on synthetic (simulated) data, as well as on real data recorded over 50 sea experiments in a variety of sea conditions. When tested on real signals, the network trained on simulated patterns showed non-trivial detection capabilities, suggesting that transfer learning can be a viable approach in these scenarios, where tagged data is often lacking. However, training the network directly on the real reflections with data augmentation techniques allowed to reach a more favorable precision-recall trade-off, approaching an ideal detection bound. We also evaluate an alternative model based on recurrent neural networks which, despite exhibiting slightly inferior performance, could be applied in scenarios requiring on-line processing of the reflection sequence. [ABSTRACT FROM AUTHOR]

The article discusses the 68th Open Seminar on Acoustics to be held from 12 to 16, September 2022 in Solina, Poland.

Deep learning techniques have the potential to address real-time source localization and seabed characterization from passive ocean acoustic signals. The challenge grows when considering single-sensor cases that lack absolute travel time with no known source or environmental parameters. To address this, convolutional neural networks (CNNs) are trained to predict the source–receiver range and the seabed type on extracted and normalized 1-s pressure time series from explosive charges measured during the 2017 Seabed Characterization Experiment. To investigate the impact of ocean variability, two training data sets containing different sets of water sound-speed profiles (SSPs) are used. CNNs trained on the first synthetic data set, which contains a static ocean depth but significant variability in water SSPs, predict seabed class more accurately than the second data set from the measured data. Conversely, CNNs trained on the second synthetic data set, which contains fewer SSPs (similar to those measured during the experiment) and multiple ocean depths, predict the source–receiver range more accurately than the first data set from the measured data. The CNNs, with a degree of uncertainty, predict the seabed type and the source range when trained on synthetic data that have been stripped of source–receiver information, such as arrival time and amplitude. The CNNs trained to only predict the seabed type also make more accurate predictions on the seabed type when compared to those for multiple prediction types. This study highlights the importance of accounting for ocean variability and prediction uncertainties in training deep learning algorithms for marine applications. [ABSTRACT FROM AUTHOR]

This article proposes a transdimensional (trans-D) geoacoustic inversion method adapted to range-dependent (RD) propagation tracks based on prior information from a high-resolution seismic survey. Most trans-D inversions to date model the seabed as a stack of range-independent homogeneous layers, with unknown geoacoustic parameters and an unknown number of layers. The proposed method models the seabed as an unknown number of homogeneous sediment layers with an RD thickness structure and applies an adiabatic normal-mode model to predict acoustic propagation. To do so, the method extrapolates trans-D seabed models proposed at the receiver position over the range of the propagation track using reflector-interface information from a seismic survey. The method is applied successfully to modal time–frequency dispersion data collected over an RD track during the 2017 Seabed Characterization Experiment (SBCEX). [ABSTRACT FROM AUTHOR]

Solving an acoustic wave equation using a parabolic approximation is a popular approach for many existing ocean acoustic models. Commonly used parabolic equation (PE) model programs, such as the range-dependent acoustic model (RAM), are discretized by the finite difference method (FDM). Considering the idea and theory of the wide-angle rational approximation, a discrete PE model using the Chebyshev spectral method (CSM) is derived, and the code is developed. This method is currently suitable only for range-independent waveguides. Taking three ideal fluid waveguides as examples, the correctness of using the CSM discrete PE model in solving the underwater acoustic propagation problem is verified. The test results show that compared with the RAM, the method proposed in this paper can achieve higher accuracy in computational underwater acoustics and requires fewer discrete grid points. After optimization, this method is more advantageous than the FDM in terms of speed. Thus, the CSM provides high-precision reference standards for benchmark examples of the range-independent PE model. [ABSTRACT FROM AUTHOR]

Active cloaking in its basic form requires that the extinction cross-section (or energy efficiency) from a radiating body vanishes. In this analysis, this physical effect is demonstrated for an active cylindrically radiating acoustic source in a non-viscous fluid, undergoing periodic axisymmetric harmonic vibrations near a rigid corner (i.e., quarter-space). The rigorous multipole expansion method in cylindrical coordinates, the method of images, and the addition theorem of cylindrical wave functions are used to derive closed-form mathematical expressions for the radiating, amplification, and extinction cross-sections of the active source. Numerical computations are performed assuming monopole and dipole modal oscillations of the circular source. The results reveal some of the situations where the extinction energy efficiency factor of the active source vanishes depending on its size and location with respect to the rigid corner, thus, achieving total invisibility. Moreover, the extinction energy efficiency factor varies between positive or negative values. These effects also occur for higher-order modal oscillations of the active source. The results find potential applications in the development of acoustic cloaking devices and invisibility in underwater acoustics or other areas. [ABSTRACT FROM AUTHOR]

The three-dimensional (3-D) sound speed structure of the ocean is a fundamental environmental element in studying underwater sound propagation modeling and forecasting. The accurate classification of the sound speed fields (SSFs) provides a comprehensive understanding and analysis of the sound propagation pattern. To take advantage of the 3-D structure of the ocean SSFs, this paper presents a quick method based on tensor decomposition for classifying the ocean 3-D SSFs. Utilizing the WOA18 dataset, High Order Iterative Orthogonal (HOOI) decomposition of the 3-D SSFs is executed so as to accurately extract the characteristic information of the SSFs. The Fuzzy C-Means clustering (FCM) method is applied to classify the feature tensors, partitioning of regional categories in different seasons and revealing the typical SSFs structures. By combining the BELLHOP model with analysis of the characteristics of the first convergence zone of each category, it is concluded that there are six categories of SSFs in the Western Pacific Ocean. The SSFs across all categories are primarily latitudinally distributed, featuring distinct sound channel axes and surface sound speed variations. • Effective extraction of tensor decomposition in sound speed fields. • Automatic tensor-based classification of sound speed fields. • Impact of typical sound speed vertical structure on sound transmission in the western Pacific Ocean. [ABSTRACT FROM AUTHOR]

The seabed data from the Kara Sea (a part of the Arctic Shelf) are used to build a low-frequency (up to 250 Hz) acoustic waveguide model and study sound propagation in this region. A 30-m deep, well-mixed, and homogenous water layer over a flat seafloor is considered. The seabed's acoustic model is based on the spatial distribution of a sound speed recorded during a three-dimensional seismic survey in the Kara Sea, as well as density data from core sample analysis. One of the region's most distinctive features is the presence of large areas (up to several tens of square kilometers) where the bottom sound speed is close to that in water. In such a setting, the normal mode approach is applied to the sound propagation problem. The overall acoustic field is made up of propagating and leaky modes, which include quasi-modes. Numerical simulations show a high spatial variability of attenuation in the waveguide, 1.5 to 20 dB/km at 137 Hz. Even if the water depth is constant and the seafloor is uniform and smooth, mode coupling and horizontal refraction can occur owing to the bottom inhomogeneities. For higher modes, the predicted angle of refraction is up to 10°. [ABSTRACT FROM AUTHOR]

The loud, impulsive, broadband underwater sounds produced during offshore pile driving are known to have auditory and behavioral effects on harbor porpoises (Phocoena phocoena) in the areas around piling sites. Thresholds to prevent behavioral effects have not yet been set, and it is unclear whether or not auditory frequency weighting of piling sounds, as used for criteria to protect hearing (Southall et al., 2019), is also useful for predicting behavioral responses and therefore required to set safety criteria and develop mitigation measures. A harbor porpoise in a pool was exposed to playbacks of piling sounds, and her behavioral responses were quantified in comparison to baseline periods without piling sounds. The full-spectrum playback piling sound was recorded at 100 m from a piling site for an offshore wind turbine. For comparison, five low-pass filtered (6.3, 3.2, 1.5, 1.0, and 0.5 kHz) versions of the sound in which the bandwidth decreased were played back at the same duty cycle (46 strikes/min) and similar single-strike sound exposure levels (power average in the pool: 135 dB re 1 qPa2s; t«>: 90 to 100 ms). As the bandwidth of the piling sounds decreased, the porpoise's behavioral response became weaker. Although these results are based on only one porpoise, they indicate that harbor porpoises respond most strongly to the higher frequencies in piling sounds. Therefore, frequency weighting of the sound exposure level (SEL) will improve prediction of behavioral responses, and behavioral response threshold levels for criteria should also be expressed as weighted SELs. However, it is unclear whether the weighting for predicting auditory effects is also the best weighting to predict behavioral effects. Mitigation of the effects of piling sounds on harbor porpoise behavior should be focused on reducing the high-frequency part of the spectrum. [ABSTRACT FROM AUTHOR]

Synchronous sampling is very essential in underwater multilinear array seismic exploration system in which every acquisition node (AN) samples analog signals by its own analog-digital converter (ADC). Aiming at the problems of complex synchronous sampling method and tang locking time alter varying sampling rate in traditional underwater seismic exploration system, an improved synchronous sampling model based on the master-slave synchronous model and local clock asynchronous drive with non phase tacked loop (PLL) is built, and a high--precision synchronous sampling method is proposed, which combines the short-term stability of local asynchronous driving dock with the master-stave synchronous calibration of local sampling dock. Based on the improved synchronous sampling model, the influence of dock stability, transmission delay and phase jitter on synchronous sampling error is analyzed, and a high-precision calibration method of synchronous sampling error based on step-by-step compensation of transmission delay is proposed. The model and method effectively realize the immunity of phase jitter on synchronous sampling error in principle, and compensate the influence of signal Transmission delay on synchronous sampling error. At the same time, it greatly reduces the complexity of software and hardware implementation of synchronous sampling, and solves the problem of long locking time after changing the sampling rate in traditional methods. The experimental system of synchronous sampling for dual linear array is built, and the synchronous sampling accuracy is better than 5 ns. [ABSTRACT FROM AUTHOR]

References 1 Xie D., Hong S., Yao C. Optimized Variational Mode Decomposition and Permutation Entropy with Their Application in Feature Extraction of Ship-Radiated Noise. Acoustics is one of the most studied fields in the 21st century, encompassing underwater acoustics, architectural acoustics, engineering acoustics, physical acoustics, environmental acoustics, psychological acoustics, signal processing in acoustics, and so on. 33922283 2 Li Y., Gao P., Tang B., Yi Y., Zhang J. Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy. [Extracted from the article]

Applications of underwater acoustics include sonar, communication, geophysical imaging, acoustical oceanography, and bioacoustics. Specialists typically work with little interdisciplinary interaction, and the terminology they employ has evolved separately in each discipline, to the point that transdisciplinary misunderstandings are common. Furthermore, increasing societal concern about possible detrimental effects of underwater noise on aquatic animals has led national and international regulators to require monitoring of underwater noise, with a consequent need for interdisciplinary harmonization of terminology. By adopting a common language, we facilitate the effective communication of concepts and information in underwater acoustics, whether for research, technology, or regulation. In the words of William H. Taft, “Don't write so that you can be understood, write so that you can't be misunderstood.” Clear definitions of widely used terms are needed, such as those used for the characterization of sound fields (e.g., “soundscape” and “ambient noise”), sound sources (“source level” and “source waveform”), sound propagation (“transmission loss” and “propagation loss”), and sound reception (“hearing threshold” and “frequency weighting function”). Terms that are used synonymously in one application have different meanings in another (examples include “hearing threshold” versus “detection threshold” and “transmission loss” versus “propagation loss”). Distinct definitions for these and many other acoustic terms are provided in a standard published in April 2017 by the International Organization for Standardization, ISO 18405. This article summarizes ISO 18405 and the process that led to the published definitions, including the reasons for omitting some terms. [ABSTRACT FROM AUTHOR]

Underwater noise analysis allows estimation of parameters of meteorological interest, difficult to monitor with in situ devices, especially in very harsh environments such as polar waters. Rainfall detection is a fundamental step of acoustical meteorology toward quantifying precipitation and, indirectly, wind. To date, this task has been conducted with some success by using a few frequency bins of the noise spectrum and combining their absolute values and slopes into some inequalities. Unfortunately, these algorithms do not perform well when applied to spectra obtained by averaging multiple noise recordings made over the course of an hour. Supervised, machine learning models allow the use of all the frequency bins in the spectrum, exploiting relationships that are difficult for a human observer to identify. Among the different models tested, a binary classifier based on random forest performed well with moderate computational load. Using a dataset consisting of over 18 000 hourly averaged spectra (approximately 25 months of in situ recordings) and comparing the results with measurements from a surface-mounted rain gauge, the proposed system detects precipitations greater than 1 mm/h with 90% probability, keeping the false alarm probability below 0.5%. This system has demonstrated remarkable robustness as performance is achieved without intentionally excluding any spectra corrupted by sounds produced by other sources, such as naval traffic and wind blowing over the sea surface. [ABSTRACT FROM AUTHOR]

Acousticvector sensors have been widely used for direction-of-arrival (DOA) estimation in hydroacoustics and aeroacoustics. The orientation of the acoustic vector sensor must be measured, e.g., by an attitude sensor, before its application to DOA estimation. However, the measured orientation generally deviates slightly from its actual orientation because of imperfect attitude measurements. This letter investigates how random deviations in the orientation degrade the performance of DOA estimation. We derive a closed-form approximation of the hybrid Cramer-Rao bound for DOA estimation by modeling the deviations as zero-mean Gaussian variables with small variances. A relationship based on a determinant-differential formula is introduced to avoid a complicated brute-force solution, yielding a sufficiently simple expression with quantitative observations. Numerical results illustrate the high accuracy and effectiveness of the closed-form approximation. [ABSTRACT FROM AUTHOR]

With the extensive application of underwater acoustic sensor networks (UANs) in various fields such as commerce, marine environmental research, and national defense, the need for an autonomous and well-organized underwater acoustic network has been increasing. Topology discovery is a crucial step in constructing an underwater acoustic network, and node discovery and topology establishment are the essential components of the topology discovery process in UANs. This paper introduces the characteristics of underwater acoustic channels and networks and highlights their influences on topology discovery. We discuss the topology discovery protocol development in terrestrial networks (i.e., duty-cycle ad hoc network, Internet of things). The main focus of this paper is to study the topology discovery protocols of UANs. This paper also classifies and introduces the existing topology discovery protocols and compared their advantages and disadvantages to understand the current topology discovery methods. Furthermore, we also discuss the topology discovery protocol’s influence on different layers’ functions in the UAN protocol stack. Analyze the current research challenges in this field, followed by important open issues in UAN protocol development, which provide new opportunities for further research. [ABSTRACT FROM AUTHOR]

Using the geometrical acoustics approximation and parabolic equation, we investigated the regularities in the spatial distribution of the acoustic field intensity generated by interaction between a caustic beam and bottom irregularities in a relatively shallow oceanic waveguide with an underwater sound channel open to the bottom. It is shown that when certain conditions are met, a multibeam structure of the spatial distribution of the acoustic field intensity is formed in the oceanic waveguide. [ABSTRACT FROM AUTHOR]

Mastering the sound propagation law of low-frequency signals in the Arctic is a major frontier basic research demand to improve the level of detection, communication, and navigation technology. It is of practical significance for long-distance sound propagation and underwater target detection in the Arctic Ocean. Therefore, how to establish an effective model to study the characteristics of the acoustic field in the Arctic area has always been a hot topic in polar acoustic research. Aimed at solving this problem, a mathematical polar acoustic field model with an elastic seafloor is developed based on a range-dependent elastic parabolic equation theory. Moreover, this method is applied to study the characteristics of polar sound propagation for the first attempt. The validity and effectiveness of the method and model are verified by the elastic normal mode method. Simultaneously, the propagation characteristics of low-frequency signals are studied in a polar sound field from three aspects, which are seafloor parameters, sea depth, and ice thickness. The results show that the elastic parabolic equation method can be well utilized to the Arctic low-frequency acoustic field. The analysis of the influence factors of the polar sound field reveals the laws of sound transmission loss of low-frequency signals, which is of great significance to provide information prediction for underwater submarine target detection and target recognition. [ABSTRACT FROM AUTHOR]

Climate change is projected to cause the Arctic soundscape to become noisier due to sea ice loss and increased anthropogenic activity. Many studies on underwater sound levels have been conducted in the western North American Arctic and Fram Strait, but the rest of the Arctic is full of geographic gaps. Han et al. (2021, https://doi.org/10.1029/2021gl093097) published a study in Geophysical Research Letters on underwater sound levels in the East Siberian Sea, providing the first estimates of seasonal trends and the natural and anthropogenic drivers of underwater sound levels in this region. This is an excellent first step in filling geographic gaps in the Russian Arctic, and I call on other researchers to continue to fill these geographic gaps throughout the Arctic so that we can set a baseline and study changes to underwater sound levels being caused directly and indirectly by climate change. Plain Language Summary: The Arctic marine environment can be one of the quietest on Earth, particularly under solid sea ice. Climate change is causing sea ice to melt at an alarming rate and is also allowing increased human shipping activity. Both sea ice loss and increased shipping activity will likely lead to a noisier environment underwater in the Arctic. Many studies have examined how loud the underwater environment is in the Arctic of western North America and between East Greenland and Svalbard, but there are many areas throughout the Arctic with no studies. Han et al. (2021, https://doi.org/10.1029/2021gl093097) just published the first study on the loudness of the underwater environment in the East Siberian Sea. This study fills an important gap in our knowledge, and I call on other researchers to continue expanding studies into areas of the Arctic where we have no data on underwater sound levels. More studies will help us track the changes in underwater sound levels being caused by climate change. Key Points: Han et al. (2021) published a study in Geophysical Research Letters on underwater sound levels in the East Siberian SeaI place this study in the context of broader effort to establish baselines of underwater sound levels in the ArcticI call on researchers to continue filling geographic gaps in studies of underwater sound levels, particularly in the Russian Arctic [ABSTRACT FROM AUTHOR]

Sonar performance prediction models require environmental inputs, including bottom depth and composition, sound-speed profile (SSP), and wave or wind conditions. Temporal and spatial variation and measurement uncertainties in environmental inputs result in uncertain model outputs. Ideally, acoustic fluctuations could be predicted from input parameter variability using a suitable modeling framework. A data set consisting of 460 SSPs and acoustic transmission loss (TL) measurements between 300 and 900 Hz was acquired during GLISTEN15, a 2015 Mediterranean Sea trial led by North Atlantic Treaty Organization's Centre for Maritime Research and Experimentation. The TL was measured in 5-min sampling periods at fixed source-to-receiver ranges of 0.5–10 km over two separate days. A gradual change in TL as large as 15 dB over 5 min was observed at some receivers and frequencies. Predicted TL variability was compared to measured TL variability by using the SSPs as inputs to an acoustic propagation model. Purely stochastic modeling either over- or underpredicted variability, depending on the temporal and spatial separation of the SSPs used as inputs. In this article, an internal wave model derived from the SSP time series was used to demonstrate the possible effect of internal waves propagating perpendicular to the source–receiver direction. The best agreement between modeled and measured variability was obtained for internal waves of 1536-s period and 0.8–1.6-m amplitude. In this way, an approach that included a physically plausible model of internal wave dynamics grounded in a few relevant in situ measurements provided good predictions of observed TL variability and a reasonable explanation of its origin. [ABSTRACT FROM AUTHOR]

The study of sound scattering from solid targets near a water–sediment interface is a topic of recent interest. Keeping in line with this direction of study, the following is an investigation of the various acoustic scattering mechanisms from a solid aluminum cylinder in broadside geometry near a flat air–water interface. In addition to identifying the possible scattering interactions that can occur, contained in this article is the explanation of the various methods utilized to investigate the different physical processes. Furthermore, the following treatment will utilize the geometrical optics approximation to treat targets as point particles to perform a simple analysis of the processes in the time domain. Although this approach is useful, it will not completely describe all aspects of the interactions but will provide a cursory understanding of the timing relations of the different identified mechanisms and will give an explanation of acoustic feature loci of a variety of possible scattering mechanisms. [ABSTRACT FROM AUTHOR]

Spherical–omnidirectional acoustic source has become a powerful tool to provide a near-ideal omnidirectional beam pattern for acoustic tests and communications. Current spherical–omnidirectional acoustic sources do not combine an omnidirectional beam pattern with a high transmitting voltage response (TVR) in the frequency range of above 200 kHz. This work presents the design, fabrication, and measurements of a high-frequency spherical–omnidirectional transducer that can provide a near-ideal omnidirectional beam pattern and a high TVR. The active element of the transducer consists of six identical square coupons with spherical curvature 1–3 piezoelectric composites operating in thickness mode. Electroacoustic responses of the fabricated transducer in water were measured. The measured resonance frequency of the transducer was 280 kHz. The maximum TVR was 161.3 dB re 1 μ Pa/V@1 m. The horizontal and vertical beamwidths of the transducer were 360° and 346°, respectively. Measurements show that the spherical piezoelectric composite transducer has a favorable spherical–omnidirectional behavior and a high TVR at high frequency. These results demonstrate that the spherical piezoelectric composite transducer is potentially a strong candidate for a high-frequency underwater acoustic source that requires an omnidirectional response. [ABSTRACT FROM AUTHOR]

One method of measuring precipitation and wind over the ocean is through analysis of the underwater ambient acoustics. In this study, the ambient ocean noises recorded by a passive aquatic listener (PAL) in the Mediterranean are used to compare the effectiveness of the machine learning techniques for measuring the wind speed and precipitation rate with the empirical methods from previous works. The data were collected over the timeframe of June 2011 to May 2012 and included two storms that caused severe coastal flooding in Genoa, Italy. A spar buoy at the surface above the PAL provided high-quality in situ measurements to act as the reference data for model training and validation. The results using the machine learning models show correlation coefficients of 0.95 between the acoustic data and wind speed and a reduction in unexplained variance by over a third from previous methods. For precipitation, CatBoost and random forest models are used to measure the total precipitation for 12 events using leave-one-event-out cross-validation, demonstrating mean errors of 28% and 34% and median errors of 18% and 17%, respectively. The ability to measure wind and precipitation by applying machine learning on data from underwater acoustic recorders shows potential to help improve in situ measurements over oceans globally. [ABSTRACT FROM AUTHOR]

As the mining of deep-sea natural deposits is becoming cost competitive compared to similar land-based mining, companies have started to dig into the seabeds to collect minerals. However, the acoustic contribution of this activity in the surrounding environment can be significant. To predict the impact of such noise, the starting point is to localize and quantify the sources that create it. In this study, a 3-D prototype acoustic array to perform this localization and quantification is designed, built, and deployed at sea for validation of its localization capacities. The design method performs a two-step study to define the array shape and select the hydrophone arrangement over it, under harsh constraints. Each step relies on two metrics to rank the candidates: the maximum sidelobe level, and the spatial resolution. These are computed on conventional beamforming maps for simulated sources that represent excavation machines on the ground. The shape is first determined to be the one that yields steady maximum sidelobe value levels over frequency. Second, the hydrophone arrangement that achieves the lowest maximum sidelobe level while limiting the spatial resolution is selected. This leads to a tip down conical array with 21 hydrophones, of about 3 m in height and diameter, and this is manufactured and used during an experimental campaign in the Mediterranean Sea. The experimental localization maps show strong agreement between the estimated source position and its ground truth. A more detailed comparison between simulated and real performances confirms accurate array conception and realization. Thus, this design procedure provides an efficient underwater acoustic array for monitoring deep-sea mining, the localization capacities of which are validated in a real-life setting. [ABSTRACT FROM AUTHOR]