Search

Evaluation of possible effects of underwater sound on aquatic life requires quantification of the sound field. A marine sound source and propagation modelling workshop took place in June 2022, whose objectives were to facilitate the evaluation of source and propagation models and to identify relevant metrics for environmental impact assessment. The scope of the workshop included model verification (model-model comparison) and model validation (model-measurement comparison) for multiple sources, including airguns, a low-frequency multi-beam echo sounder, and a surface vessel. Several verification scenarios were specified for the workshop; these are described herein. [ABSTRACT FROM AUTHOR]

Dedicated coating materials for anechoism and furtivity in underwater acoustics must exhibit a strong reliability regarding their mechanical resistance to hydrostatic pressure. Soft porous materials, especially, a distribution of soft porous beads within a polyurethane matrix, have been previously proposed as an acoustic insulator device. The purpose of the present letter is to investigate the attenuation efficiency of soft porous silicone beads-based materials while being exposed to uniaxial loads mimicking hydrostatic pressures encountered in underwater acoustics. The acoustic performance of this locally resonant material is then compared to the classical coating technology using micro-balloons. The use of an adapted surfactant (a silicone alkyl polyether compound) in the fabrication process of the soft porous silicone-based beads, obtained through an emulsion templating process, leads to particles exhibiting an open porosity. The (resonant) attenuation of the soft porous beads-based material remains greater than the micro-balloons-based material until several bars. Above this critical resilience value, the mechanical stress irreversibly damages the soft porous beads. [ABSTRACT FROM AUTHOR]

The model manifold, an information geometry tool, is a geometric representation of a model that can quantify the expected information content of modeling parameters. For a normal-mode sound propagation model in a shallow ocean environment, transmission loss (TL) is calculated for a vertical line array and model manifolds are constructed for both absolute and relative TL. For the example presented in this paper, relative TL yields more compact model manifolds with seabed environments that are less statistically distinguishable than manifolds of absolute TL. This example illustrates how model manifolds can be used to improve experimental design for inverse problems. [ABSTRACT FROM AUTHOR]

Passive detection of target-of-interest (TOI) within strong interferences poses a challenge. This paper introduces an adaptive interference suppression based on an invariant subspace of matrix matching. Assume that the TOI-bearing intervals are known. We define a correlation ratio for each eigenvector to obtain the highest one. Then, we use invariant subspace of matrix matching to measure the distance between two invariant projection matrices of this eigenvector. This identifies and removes the eigenvectors associated with TOI. Finally, the remaining eigenvectors are subtracted from the sample covariance matrix to suppress interference and noise. The viability of the proposed method is demonstrated experimentally. [ABSTRACT FROM AUTHOR]

An underwater acoustic recorder was moored off Heard Island from September 2017 through March 2018 to listen for marine mammals. Analysis of data was initially conducted by visual inspection of long-term spectral averages to reveal sounds from sperm whales, Antarctic and pygmy blue whales, fin whales, minke whales, odontocete whistles, and noise from nearby ships. Automated detection of sperm whale clicks revealed they were seldom detected from September through January (n = 35 h) but were detected nearly every day of February and March (n = 684 h). Additional analysis of these detections revealed further diel and demographic patterns. [ABSTRACT FROM AUTHOR]

The probability distribution of three-dimensional sound speed fields (3D SSFs) in an ocean region encapsulates vital information about their variations, serving as valuable data-driven priors for SSF inversion tasks. However, learning such a distribution is challenging due to the high dimensionality and complexity of 3D SSFs. To tackle this challenge, we propose employing the diffusion model, a cutting-edge deep generative model that has showcased remarkable performance in diverse domains, including image and audio processing. Nonetheless, applying this approach to 3D ocean SSFs encounters two primary hurdles. First, the lack of publicly available well-crafted 3D SSF datasets impedes training and evaluation. Second, 3D SSF data consist of multiple 2D layers with varying variances, which can lead to uneven denoising during the reverse process. To surmount these obstacles, we introduce a novel 3D SSF dataset called 3DSSF, specifically designed for training and evaluating deep generative models. In addition, we devise a high-capacity neural architecture for the diffusion model to effectively handle variations in 3D sound speeds. Furthermore, we employ state-of-the-art continuous-time-based optimization method and predictor-corrector scheme for high-performance training and sampling. Notably, this paper presents the first evaluation of the diffusion model's effectiveness in generating 3D SSF data. Numerical experiments validate the proposed method's strong ability to learn the underlying data distribution of 3D SSFs, and highlight its effectiveness in assisting SSF inversion tasks and subsequently characterizing the transmission loss of underwater acoustics. [ABSTRACT FROM AUTHOR]

The conversion from seismic to ocean-acoustic waves occurs in different places on the bottom of the ocean, often hundreds to thousands of kilometers away from the epicenter. Here, we investigate this conversion process by studying 15 large-magnitude earthquakes that occurred between 2014 and 2022 along the Kermadec Arc in the southwestern Pacific Ocean. To pinpoint the location where seismic-to-acoustic conversion takes places, we analyze hydroacoustic signals recorded by a hydrophone triplet station of the International Monitoring System in the Juan Fernández archipelago. Results from direction-of-arrival and travel-time calculations indicate that the location of the conversion zone largely matches segments of the Louisville Seamount Chain, its lateral extent ranging from approximately 300 to 1800 km, and its location depending on the geometry between earthquake epicenter and the seamounts. [ABSTRACT FROM AUTHOR]

Sound speed is a critical parameter in ocean acoustic studies, as it determines the propagation and interpretation of recorded sounds. The potential for exploiting oceanic vessel noise as a sound source of opportunity to estimate ocean sound speed profile is investigated. A deep learning-based inversion scheme, relying upon the underwater radiated noise of moving vessels measured by a single hydrophone, is proposed. The dataset used for this study consists of Automatic Identification System data and acoustic recordings of maritime vessels transiting through the Santa Barbara Channel between January 2015 and December 2017. The acoustic recordings and vessel descriptors are used as predictors for regressing sound speed for each meter in the top 200 m of the water column, where sound speeds are most variable. Multiple (typically ranging between 4 and 10) transits were recorded each day; therefore, this dataset provides an opportunity to investigate whether multiple acoustic observations can be leveraged together to improve inversion estimates. The proposed single-transit and multi-transit models resulted in depth-averaged root-mean-square errors of 1.79 and 1.55 m/s, respectively, compared to the seasonal average predictions of 2.80 m/s. [ABSTRACT FROM AUTHOR]

Predicting acoustic transmission loss in the SOFAR channel faces challenges, such as excessively complex algorithms and computationally intensive calculations in classical methods. To address these challenges, a deep learning-based underwater acoustic transmission loss prediction method is proposed. By properly training a U-net-type convolutional neural network, the method can provide an accurate mapping between ray trajectories and the transmission loss over the problem domain. Verifications are performed in a SOFAR channel with Munk's sound speed profile. The results suggest that the method has potential to be used as a fast predicting model without sacrificing accuracy. [ABSTRACT FROM AUTHOR]

Acoustic propagation through a random distribution of 1 m ice cubes, from 100 to 1000 Hz, was simulated in a 3D finite element model. The effective sound speed and attenuation as functions of frequency were calculated from the simulated signals. Attempts were made to fit a number of models to the wave speed and attenuation, including single scattering, lossy water, and Biot approximations. An extended Biot model, developed for acoustic propagation in granular seabed sediments, was able to fit the simulation up to 300 Hz. Beyond this frequency, the simulation shows that multiple scattering dominates. [ABSTRACT FROM AUTHOR]

The underwater broadband anechoic coating is highly demanded in acoustic stealth for underwater vehicles. In this work, we propose a gradient index metamaterial for broadband underwater sound absorption, which is further experimentally validated under high pressure conditions. The gradient index metamaterial consisting of radius-varied cavities in rubber allows the sound waves to follow the objective trajectory in a broad band with impedance matching at the interface with water. The viscosity of the materials and the coupling effect among the gradient cavities contribute to broadband sound absorption. The performance of broadband sound absorption from 1 to 10 kHz is validated experimentally, which agrees well with the theoretical and numerical results. We further experimentally demonstrate the sound absorption performance with hydrostatic pressure up to 3 MPa and analyze the mechanism of the sound absorption deviation caused by high pressures. The proposed gradient index metamaterial provides a simple and efficient way to develop underwater broadband acoustic coatings. [ABSTRACT FROM AUTHOR]

We propose a contactless and non-closed strategy to mitigate the sound radiated from an underwater source. The problem is formulated as the interaction of the source with different cross-sectional shapes (including ideal zero-cross-section sources, circular-cross-section rods, and rectangular-cross-section rods) and the acoustic superscatterer treated as a concentric cylindrical structure. The acoustic superscatterer consisting of an internal core and a coating made of the double-negative acoustic metamaterial with specific constitutive parameters relies on the coating to virtually magnify its internal core, thus yielding intense multiple scattering with the source. According to the transformation media theory and the method of images, the complete landscape has been presented theoretically and numerically of the remote mitigation of underwater source radiation via an acoustic superscatterer. We demonstrate that by appropriately placing the acoustic superscatterer nearby the source, it can achieve the omnidirectional radiation mitigation stemming from the coherent extinction mechanism. A possible scheme for the practical realization of the acoustic superscatterer is also discussed. This work may facilitate the design and application of remotely placed meta-devices for the manipulation of underwater acoustic waves. [ABSTRACT FROM AUTHOR]

A numerical demonstration is given of the feasibility of a newly designed tunable asymmetric acoustic transmission device, for which the acoustic transmission coefficients for perpendicularly incident left- and right-running waves are different at a particular single frequency within a forbidden zone. The proposed device consists of a hybrid, sonic-crystal-based resonant structure with horizontal periodicity and a one-dimensional periodic rectangular acoustic grating with vertical periodicity. The former structure exhibits a wide bandgap through which only waves with particular combinations of their frequency and propagation direction can tunnel. The direction dependence of the acoustic transmission is based on the geometrical asymmetry of the placement of the grating, and on the narrowband correspondence between the diffraction angle of the grating and the allowed transmission direction through the sonic-crystal-based structure. Angular and spectral tuning are possible by changing the grating and/or the sonic crystal periodicity. The device has potential applications in underwater acoustics for asymmetric transmission systems and secure communication systems. [ABSTRACT FROM AUTHOR]

Accurately identifying sources of flow loss and hydroacoustics and clarifying the mechanism of their generation are crucial for directing the optimal design of efficient and quiet pump-jet propulsors (PJPs). In this paper, numerical simulations of steady and unsteady flow are performed for a PJP equipped with pre-swirl stationary vanes, based on which both sources of flow loss and hydroacoustics are investigated at multi-level granularity. Analyses of flow efficiency and entropy generation rate are performed to identify the sources of flow loss, and analyses of thrust fluctuation and wall pressure fluctuation are conduced to identify the sources of hydroacoustics. The results indicate that the pressure drag accounts for 76% of the total drag and is mainly contributed from the stator and the duct, but the flow efficiency of the rotor is much smaller than that of the stator and the sources of the flow loss are mainly located at three regions of the rotating blades: the leading edge, the tip, and the corner of the suction surface. The hydroacoustic sources are mainly located at the leading edge and the tip of the rotating blades due to stator–rotor and duct–rotor interactions, respectively, but the Taylor's frozen turbulence hypothesis is inappropriate to describe the wake evolution of the stationary vanes owing to the potential interaction caused by the blade rotation. [ABSTRACT FROM AUTHOR]

Bubble entrainment caused by and underwater sound produced by a single water drop falling on the surface of freshwater and saltwater were experimentally investigated in this study. A charge-coupled device camera was employed to photograph the drop's impact and the process of bubble formation. Underwater sound was received using a hydrophone connected to a charge amplifier and a data-acquisition system. To capture the temporal and spectral characteristics of the sound, the time series of the underwater sound was transformed into the time–frequency domain by using the Gabor transform. The diameter of the drops was varied from 2.6 to 5.66 mm, and the release heights investigated were 10–150 cm. The experimental results revealed three distinct bubble formation processes following the impact of a water drop. Type-I bubbling was the formation of a singular bubble at the apex of the contracting crater produced by the initial drop impact. Type-II bubbling was the formation of one or multiple bubbles entrained by the downward motion of the water column produced during the initial drop impact. Type-III bubbling was the formation of a singular bubble generated due to the impact of a secondary water drop above the water column. The effects of salinity on bubble entrainment and underwater noise were also studied. For the same experimental parameters, bubbles entrained in saltwater were discovered to be larger than those entrapped in freshwater; moreover, the saltwater bubbles collapsed into two bubbles. [ABSTRACT FROM AUTHOR]

The stochastic dynamically orthogonal (DO) narrow-angle parabolic equations (NAPEs) are exemplified and their properties and capabilities are described using three new two-dimensional stochastic range-independent and range-dependent test cases with uncertain sound speed field, bathymetry, and source location. We validate results against ground-truth deterministic analytical solutions and direct Monte Carlo (MC) predictions of acoustic pressure and transmission loss fields. We verify the stochastic convergence and computational advantages of the DO-NAPEs and discuss the differences with normal mode approaches. Results show that a single DO-NAPE simulation can accurately predict stochastic range-dependent acoustic fields and their non-Gaussian probability distributions, with computational savings of several orders of magnitude when compared to direct MC methods. With their coupling properties and their adaptation in range to the dominant uncertainties, the DO-NAPEs are shown to predict accurate statistics, from mean and variance to multiple modes and full probability distributions, and to provide excellent reconstructed realizations, from amplitudes and phases to other specific properties of complex realization fields. [ABSTRACT FROM AUTHOR]

The loss of Arctic sea ice is one of the most visible signs of global climate change. As Arctic sea ice has retreated, Arctic marine shipping has increased. The Pan-Arctic's unique underwater acoustic properties mean that even small increases in ship traffic can have a significant effect on the ambient soundscape. This study presents the first long-term, basin-scale model of shipping noise in the Pan-Arctic with a focus on a few select sub-regions. The Arctic Ship Traffic Database from the Protection of the Arctic Marine Environment is used in this study to model the locations and source levels from ships operating in the Pan-Arctic between 2013 and 2019. The acoustic footprint of these ships is explored temporally for the entire basin as well as for the select large maritime ecosystems of the Barents Sea, the Northern Bering-Chukchi Sea, and Baffin Bay. From 2013 to 2019, modeled shipping noise propagating underwater broadly increased between 5–20 dB across the Pan-Arctic, but more specific results in sub-regions are presented and discussed. [ABSTRACT FROM AUTHOR]

This manuscript presents a method for reproducing sound fields actively by using a vibrating submerged structure as the field reproduction source, with the target sound field to be reproduced defined in the frequency domain using the acoustic brightness approach. To balance the predetermination of a mono- or multi-zone target sound pressure field and the control effort required, singular value decomposition of the structural-acoustic system matrix is proposed. The dependency of the radiation efficiency into the target zone on the singular modes representing source and pressure modes is investigated using a wavenumber-domain approach. Furthermore, a feedforward control principle is adopted for adaptive sound-field reproduction with mode matching from the least squares perspective. Finally, an experiment is reported that involve synthesizing a tonal target underwater acoustic signature of a model of a fast attack craft (scale 1:8) at a measurement facility at Lake Plön in Germany. The results show that with the structural-acoustic brightness approach structural modes with radiation coupling into the target zone are excited and related pressure modes exhibit individual focus in the direction of hydrophones in use. Finally, a predetermined narrowband sound pressure field is actively reproduced at the hydrophone positions using inertial actuators and accelerometers on the ship model's hull. [ABSTRACT FROM AUTHOR]

Robust informative acoustic predictions require precise knowledge of ocean physics, bathymetry, seabed, and acoustic parameters. However, in realistic applications, this information is uncertain due to sparse and heterogeneous measurements and complex ocean physics. Efficient techniques are thus needed to quantify these uncertainties and predict the stochastic acoustic wave fields. In this work, we derive and implement new stochastic differential equations that predict the acoustic pressure fields and their probability distributions. We start from the stochastic acoustic parabolic equation (PE) and employ the instantaneously-optimal Dynamically Orthogonal (DO) equations theory. We derive stochastic DO-PEs that dynamically reduce and march the dominant multi-dimensional uncertainties respecting the nonlinear governing equations and non-Gaussian statistics. We develop the dynamical reduced-order DO-PEs theory for the Narrow-Angle parabolic equation and implement numerical schemes for discretizing and integrating the stochastic acoustic fields. [ABSTRACT FROM AUTHOR]

Piezoelectric composite materials (PCMs) with shunt damping circuits are used widely in hydroacoustics because of the flexible adjustability of their parameters. PCMs offer good underwater sound absorption, but shortcomings remain, such as poor low-frequency sound absorption, narrow bandwidth, and a single dissipation mechanism. In this paper, the tunable underwater sound absorption of a 0–3 PCM combined with a cavity structure and shunt circuit (PCMC) is studied systematically. First, the equivalent material parameters of 0–3 PCM are derived based on the Yamada model, and then a theoretical electroacoustic model is established for solving the absorption coefficient and is mutually verified with the numerical simulation method. On this basis, the tunable absorption characteristics of the structure are analyzed. The results show that coupling the energy dissipation mechanism of 0–3 PCM with the acoustic mechanism of the cavity structure not only achieves strong absorption at lower frequencies but also enriches the absorption mode in the mid-high frequencies by connecting the shunt circuits. Moreover, the influence of piezoelectric control variables and acoustic cavity morphology characteristics on structural sound absorption performance is further explored. Finally, the acoustic performance of PCMC is improved further via shape optimization and parameter optimization. [ABSTRACT FROM AUTHOR]

It is challenging to construct generalized physical models of underwater wave propagation owing to their complex physics and widely varying environmental parameters and dynamical scales. In this article, we present a deep convolutional recurrent autoencoder network (CRAN) for data-driven learning of complex underwater wave scattering and interference. We specifically consider the dynamics of underwater acoustic scattering from various non-uniform seamount shapes leading to complex wave interference patterns of back-scattered and forward-propagated waves. The CRAN consists of a convolutional autoencoder for learning low-dimensional system representation and a long short-term memory (LSTM)-based recurrent neural network for predicting system evolution in low dimensions. The convolutional autoencoder enables efficient dimension reduction of wave propagation by independently learning global and localized wave features. To improve the time horizon of wave dynamics prediction, we introduce an LSTM architecture with a single-shot learning mechanism and optimal time-delayed data embedding. On training the CRAN over 30 cases containing various seamount geometries and acoustic source frequencies, we can predict wave propagation up to a time horizon of 5 times the initiation sequence length for 15 out-of-training cases with a mean L2 error of approximately 10%. For selected out-of-training cases, the prediction time horizon could be increased to 6 times the initiation sequence length. Importantly, such predictions are obtained with physically consistent wave scattering and wave interference patterns and at 50% lower L2 error compared to routinely use standard LSTMs. These results demonstrate the potential of employing such deep neural networks for learning complex underwater ocean acoustic propagation physics. [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]

Developing an effective and robust representation model for ocean sound speed profiles (SSPs) is crucial for numerous ocean acoustic applications. However, the performance of existing sound speed profile (SSP) representation methods, such as empirical orthogonal function and K-singular value decomposition, heavily relies on the number of selected basis functions. This could lead to overfitting of noise, as these methods are unable to distinguish between signals and noise during the basis function learning process. To overcome these limitations and effectively learn a large number of basis functions with strong representation power from potentially noisy SSP data, we propose a novel algorithm called deep matrix decomposition (deep MD). This algorithm utilizes untrained deep neural networks as priors to reject noise within the interpretable matrix decomposition framework. To achieve optimal performance with deep MD, we propose a stopping strategy based on the rank estimate to determine the termination epoch. Experimental results using real-life datasets demonstrate that deep MD is robust against various types of noise and outperforms traditional SSP representation methods in terms of SSP reconstruction and characterizing the transmission loss in underwater acoustics. [ABSTRACT FROM AUTHOR]

Thin-shell models offer important insights into the complex process of sound-structure interaction but are found to be inconsistent with the rigorous thick-shell theory for fluid-loaded spherical shells. Here, linearized equations of motion of fluid-loaded, thin, spherical shells are re-derived from the first principles. The shell may be prestressed due to the difference in the static pressures in the internal and external fluids. Differences in the fluid-loading terms from previously proposed ad hoc models are identified and their significance is analyzed. Analytic solutions are derived of the problems of spherical sound wave scattering by a fluid-filled, prestressed spherical shell and resonant vibrations of the shell. The results reduce to a number of known exact and asymptotic solutions in appropriate limiting cases. The mathematical model of the shell vibrations is applied to characterize the influence of the shell's material properties and the prestress on passive suppression of low-frequency underwater sound radiation due to diffraction on an acoustically compliant sphere, such as an encapsulated gas bubble. Using soft rubber as the encapsulating membrane is found to preserve the sound suppression qualities of the free gas bubble. [ABSTRACT FROM AUTHOR]

We present a sensing modality using the geometric phase of acoustic waves propagating in an underwater environment. We experimentally investigate the effect of scattering by a small subwavelength perturbation on a flat submerged surface. We represent the state of an acoustic field in the unperturbed and perturbed cases as multidimensional vectors. The change in geometric phase is obtained by calculating the angle between those vectors. This angle represents a rotation of the state vector of the wave due to scattering by the perturbation. We perform statistical analysis to define a signal-to-noise ratio to quantify the sensitivity of the geometric phase measurement and compare it to magnitude based measurements. This geometric phase sensing modality is shown to have higher sensitivity than the magnitude based sensing approach. [ABSTRACT FROM AUTHOR]

Mesoscale vorticity is an important factor that affects the non-uniform horizontal and vertical distribution of hydrologic elements in the ocean. In this paper, temperature and salinity data from measured mesoscale cold-core eddies during a voyage within a certain sea area are studied, and a synchronous sound field test was conducted on the mesoscale vorticity. Based on the temperature and salinity data, the parabolic equation (PE) method was selected to predict the acoustic field, and the results were compared with the measured propagation loss data of the acoustic field to verify the accuracy and effectiveness of the PE model. The underwater sound propagation characteristics in the mesoscale cold-core eddy environment were then analyzed using the temperature and salinity data retrieved from the voyage. It was found that the convergence area of the acoustic field gradually dispersed with an increase in the depth of the sound source. In a mesoscale eddy environment, when sound waves propagate from inside to outside the eddy, the presence of a cold-core eddy causes the convergence area to shift toward the edge of the eddy, and the deviation gradually decreases with an increase in the depth of the sound source. [ABSTRACT FROM AUTHOR]

Ships unintentionally radiate underwater noise mainly due to propeller cavitation under usual operations. In 2022, the International Maritime Organization started a review of the nonmandatory guidelines for the reduction of underwater radiated noise (URN) from ships. The characteristics of URN from ships have been studied for a long time, and quantitative variations in URN levels with ship size and speed have been reported. From the viewpoint of ship design, it is more reasonable that the effect of ship speed and draft is considered as the ratio to design speed and maximum draft, respectively. Therefore, in this study, underwater sound measurements were conducted in deep water (>300 m in depth) under a sea lane, and regression analysis was applied to the source levels of the URN from many merchant ships using ship length, ship speed ratio to design speed, and draft ratio to maximum draft. In this analysis, the source level is simplified based on the characteristics of URN due to propeller cavitation. This allows one coefficient to represent the approximate shape of the spectrum of URN level. Further, variations in the URN level for each ship type are discussed based on the results and comparisons with previous studies. [ABSTRACT FROM AUTHOR]

Odontocetes have developed a broadband sound reception system that performs well underwater. We used aluminum materials and soft silica gels to fabricate a bio-receptor to mimic the sound reception system of a finless porpoise. Both numerical modeling and experiments suggested that compared to omnidirectional reception, the porpoise-inspired receptor can achieve broadband and directional sound reception with frequencies ranging from 15 to 90 kHz and enhance the reception by an average of 3.9 dB in this bandwidth. At some frequencies, this reception improvement can reach 7.3 dB in experimental data. This work provides an alternate idea to design sound receptors to be applied in underwater broadband and directional sound reception. [ABSTRACT FROM AUTHOR]

A Luneburg lens is a gradient refractive index lens that can focus plane waves on a point at the perimeter without aberration. Three-dimensional (3D) Luneburg lens for airborne sound has been well investigated in recent years. However, constructing a 3D Luneburg lens for underwater sound is a challenging task due to the difficulties in the designing and fabricating of the desired isotropic underwater acoustic materials. This work presents the practical implementation of a 3D Luneburg lens for underwater sound. Such a 3D Luneburg lens is designed based on 3D gradient face-centered-cubic phononic crystals, which have quasi-isotropic refractive index patterns and can be fabricated with photosensitive resin by 3D printing. The experimental results show that the lens can realize the omnidirectional imaging of underwater sound from 30 to 38 kHz. This 3D underwater acoustic Luneburg lens may prompt the potential applications in underwater acoustic wide-angle retroreflectors, sonars, and biomedical imaging devices. [ABSTRACT FROM AUTHOR]

Acoustic asymmetrical transmission is a theoretical and engineering challenge because of the reciprocity of the linear acoustic wave equation. It can be achieved by systems breaking reciprocity or by reciprocal systems relying solely on spatial symmetry breaking. Metagratings are planar structures relying on Bragg's diffraction to reroute wave energy toward a desired direction and are eventually able to achieve asymmetrical transmission when build from an asymmetrical pattern of multiple basic elements. The challenge for water-like media is to combine the geometrical complexity of the structure with good acoustic impedance contrast and practical feasibility. In this work, we build a reciprocal metagrating from brass cylinders arranged according to a numerically optimized pattern and obtain highly efficient asymmetrical transmission for underwater acoustic waves. Around 200 kHz, the structure transmits nearly all incident energy toward a 45° angle when insonified from one side, but act as a near perfect reflector when insonified from the other. The effect relies entirely on the simple phenomena of linear wave diffraction and interference. The generality and efficiency of this device could be of interest for applications in underwater acoustics or medical ultrasounds. [ABSTRACT FROM AUTHOR]

Masking can reduce the efficiency of communication and prey and predator detection. Most underwater sounds fluctuate in amplitude, which may influence the amount of masking experienced by marine mammals. The hearing thresholds of two harbor seals for tonal sweeps (centered at 4 and 32 kHz) masked by sinusoidal amplitude modulated (SAM) Gaussian one-third octave noise bands centered around the narrow-band test sweep frequencies, were studied with a psychoacoustic technique. Masking was assessed in relation to signal duration, (500, 1000, and 2000 ms) and masker level, at eight amplitude modulation rates (1–90 Hz). Masking release (MR) due to SAM compared thresholds in modulated and unmodulated maskers. Unmodulated maskers resulted in critical ratios of 21 dB at 4 kHz and 31 dB at 32 kHz. Masked thresholds were similarly affected by SAM rate with the lowest thresholds and the largest MR being observed for SAM rates of 1 and 2 Hz at higher masker levels. MR was higher for 32-kHz maskers than for 4-kHz maskers. Increasing signal duration from 500 ms to 2000 ms had minimal effect on MR. The results are discussed with respect to MR resulting from envelope variation and the impact of noise in the environment on target signal detection. [ABSTRACT FROM AUTHOR]

The potential effects of underwater anthropogenic sound and substrate vibration from offshore renewable energy development on the behavior, fitness, and health of aquatic animals is a continuing concern with increased deployments and installation of these devices. Initial focus of related studies concerned offshore wind. However, over the past decade, marine energy devices, such as a tidal turbines and wave energy converters, have begun to emerge as additional, scalable renewable energy sources. Because marine energy converters (MECs) are not as well-known as other anthropogenic sources of potential disturbance, their general function and what is known about the sounds and substrate vibrations that they produce are introduced. While most previous studies focused on MECs and marine mammals, this paper considers the potential of MECs to cause acoustic disturbances affecting nearshore and tidal fishes and invertebrates. In particular, the focus is on particle motion and substrate vibration from MECs because these effects are the most likely to be detected by these animals. Finally, an analysis of major data gaps in understanding the acoustics of MECs and their potential impacts on fishes and aquatic invertebrates and recommendations for research needed over the next several years to improve understanding of these potential impacts are provided. [ABSTRACT FROM AUTHOR]

The initial discharge process of plasma electrolytic oxidation (PEO) on the 60 vol. % SiCP/2009 aluminum matrix composite in silicate solution was in situ monitored by sound and vibration measurement techniques. The underwater sound, airborne sound, and sample vibration signals were detected in the initial 120 s of the PEO process, and their generation mechanism was discussed. In terms of waveforms and spectrograms of the sound and vibration signals, the initial PEO process can be divided into five stages: conventional anodizing stage (I), glow discharge stage (Ⅱ), tiny spark discharge stage (Ⅲ), large spark discharge stage (Ⅳ), and strong spark discharge stage (Ⅴ). The sound and vibration signals during the PEO process are attributed to the evolution of bubbles, which are from the plasma discharge, electrochemical reactions, and vaporization of electrolyte under Joule heat. In stage I, these signals completely come from the bubbles produced by the evaporative electrolyte and electrochemical reactions. In stages Ⅱ–Ⅴ, the bubbles from the plasma discharge gradually become the main source of these signals with increasing discharge intensity. In addition, the spike peaks on the waveforms of these signals at stage Ⅴ are related to the strong discharge sparks. These results demonstrate that sound and vibration measurement techniques can effectively monitor the PEO discharge process. [ABSTRACT FROM AUTHOR]

A radiation transport equation that describes the spatiotemporal evolution of the directional spectrum of underwater acoustic noise is presented and applied to ship noise. A ray-based algorithm is used to solve the transport equation and numerically simulate the evolution of the directional noise spectrum produced by a passing ship. The model described accounts for the transient and highly episodic nature of shipping noise, the strong anisotropy of the radiated shipping noise, the directional dependence of the resulting acoustic field, and the critical angle dependence of bottom-reflected energy. The model predicts time histories of sound pressure level and directional spectral energy density at distant locations if the ship track and the ship's radiated noise power are known. Simulations are shown to be in qualitatively good agreement with observations. [ABSTRACT FROM AUTHOR]

Unoccupied aerial vehicles (UAVs), or "drones," are increasingly used as a tool for cetacean research, but knowledge about how these tools contribute to underwater sound is lacking. In this study, underwater sound levels of three commonly used UAV models (Mavic Pro Platinum, Phantom 4 Pro v2.0, Inspire 1 Pro) were recorded. For each model, three replicate flights were conducted at 36 positions at standardized horizontal (0–30 m) and vertical (2–40 m) distances from a hydrophone (1 m depth). Median broadband received levels of the Inspire were highest at 96.5 dBrms 141–17 783 Hz re 1 μPa2, followed by the Phantom (92.4 dBrms 141–17 783 Hz re 1 μPa2) and Mavic, which was quietest (85.9 dBrms 141–17 783 Hz re 1 μPa2). Median ambient sound levels in the absence of an UAV were 82.7 dBrms 141–17 783 Hz re 1 μPa2. Significant increases in ambient sound levels associated with UAV flights occurred at higher altitudes than previously reported, and received levels decreased more with increasing horizontal distance of the UAV than with altitude. To minimize potential noise impacts on sensitive marine animal subjects, we recommend increasing horizontal distance to the animal, rather than altitude, and choosing the quietest UAV feasible. [ABSTRACT FROM AUTHOR]

Supervised machine learning (ML) is a powerful tool that has been applied to many fields of underwater acoustics, including acoustic inversion. ML algorithms depend on the existence of extensive labeled datasets, which are difficult to obtain for the task of underwater source localization. A feed-forward neural network (FNN) trained on imbalanced or biased data may end up suffering from a problem analogous to model mismatch in matched field processing (MFP), that is, producing incorrect results due to a difference between the environment sampled by the training data and the actual environment. To overcome this issue, physical and numerical propagation models can act as data augmentation tools to compensate for the lack of comprehensive acoustic data. This paper examines how modeled data can be effectively used for training FNNs. Mismatch tests compare the output from a FNN and MFP and show that the network becomes more robust to various kinds of mismatches when trained on diverse environments. A systematic analysis of how the training dataset's variability impacts a FNN's localization performance on experimental data is carried out. Results show that networks trained with synthetic data achieve better and more robust performance than regular MFP when environment variability is taken into account. [ABSTRACT FROM AUTHOR]

Increasing the number of closely packed air bubbles immersed in water changes the frequency of the Minnaert resonance. The collective interactions between bubbles in a small ensemble are primarily in the same phase, causing them to radiate a spherically symmetric field that peaks at a frequency lower than the Minnaert resonance for a single bubble. In contrast, large periodic arrays include bubbles that are further apart than half of the wavelength such that collective resonances have bubbles oscillating in opposite phases, ultimately creating a fundamental resonance at a frequency higher than the single-bubble Minnaert resonance. This work investigates the transition in resonance behavior using a modal analysis of a mass-spring system and a boundary element method. The computational complexity of the full-wave solver is significantly reduced to a linear dependence on the number of bubbles in a rectangular array. The simulated acoustic fields confirm the initial downshift in resonance frequency and the strong influence of collective resonances when the array has hundreds of bubbles covering more than half of the wavelength. These results are essential in understanding the low-frequency resonance characteristics of bubble ensembles, which have important applications in diverse fields such as underwater acoustics, quantum physics, and metamaterial design. [ABSTRACT FROM AUTHOR]

Acoustic scattering and resonances of gas bubbles are computed using a time-domain simulation based on numerical solutions of the conservation laws. The time histories of scattered pressure and fluid velocity, outside and inside the bubble, are obtained simultaneously from an immersed-boundary method allowing for the investigation of exterior and interior fields for non-spherical geometries. The acoustic resonances of the bubble are investigated for various bubble sizes, shapes, and inner gas parameters and compared in limiting cases to the partial wave scattering solutions for spherical bubbles. The dynamics of the gas motion and its associated contribution to resonance response has received little attention in previous analytical and numerical formulations. In this study, the acoustic propagation and motion inside the interior gas is investigated with respect to the monopole resonance with the combined time-domain simulation and immersed-boundary method. For the non-spherical prolate and oblate shapes, the scattering and resonance behaviors are compared with the approximate analytical results based on the shape factor method. The simulation method can be extended to less-understood shapes relevant to underwater and physical acoustics, such as "pancake-shaped" or "cigar-shaped" bubbles, as well as to spatial and time-dependent forcing. [ABSTRACT FROM AUTHOR]

A coupled-mode model is a classic approach for solving range-dependent sound propagations and is often used to provide benchmark solutions in comparison with other numerical models because of its high accuracy. Existing coupled-mode programs have disadvantages such as high computational cost, weak adaptability to complex ocean environments, and numerical instability. In this paper, a new algorithm that uses an improved range normalization of a "stair-step" and global matrix approach to address range dependence in ocean environments is designed. This algorithm uses the Chebyshev–Tau spectral method to solve the eigenpairs in the range-independent segments. The Chebyshev–Tau spectral method can converge rapidly, and the rate of convergence depends on the smoothness of the sound speed and density profiles. The main steps of the algorithm are parallelized, so parallel computing technologies are also applied for further acceleration. Based on this algorithm, an efficient program is implemented, and numerical simulations verify that this algorithm is reliable, accurate, and capable. Compared with the existing coupled-mode programs, the newly developed program is more stable and efficient with comparable accuracy and can simulate waveguides in more complex and realistic ocean environments. [ABSTRACT FROM AUTHOR]

Topological insulators provide a new route to design acoustic metamaterials, which can exhibit novel propagation properties. However, most of the current topological acoustic metamaterials are characterized by a passive response and operated at fixed frequency ranges, and there are few reports on the effect of temperature of water on acoustic topological insulators. Therefore, in this paper, we design the temperature-controlled tunable underwater acoustic topological insulators. The topological acoustic system is composed of a triangular array of triangular steel columns embedded in water. We calculate the Dirac point frequencies and bulk band structures at different temperatures. The results show that the topological nontrivial bandgap frequency range is very sensitive to the temperature of water. We also use some numerical examples to demonstrate the robustness and defect-immune properties of the topological phononic crystals, and the topological properties can be switched by controlling the temperature of water. Our study shows that the change in the temperature can behave as an acoustic switch, which may have applications in the underwater sound waveguide as well as underwater communications. [ABSTRACT FROM AUTHOR]

We proposed an acoustic metamaterial with deep subwavelength thickness for low-frequency underwater sound absorption. The proposed hybrid metamaterial has a perforated facesheet, a fluid-filled square honeycomb core with inside rubber coating, and a fixed backsheet. A theoretical model is established to predict the sound absorption performance of this perforated honeycomb hybrid metamaterial based on the sound absorption theory of the micro-perforated panel and electro-acoustic analogy. The theoretical model agrees well with our finite element simulation. Results suggest that perfect sound absorption (99.9%) of the metamaterial occurs at 375 Hz, at which the thickness of the metamaterial is only 1/80 of the underwater sound wavelength. According to the simulation, most of the sound energy is consumed by the rubber coating. It can be analyzed that the rubber coating replaces the fluid in the square honeycomb resonant cavity improving the acoustic capacitance and acoustic resistance and triggering a quasi-Helmholtz resonance. This acoustic metamaterial also exhibits a broadband underwater sound absorption performance by parallel design with different perforations, which has a promising potential in engineering applications. [ABSTRACT FROM AUTHOR]

In the field of aviation anti-submarine warfare, magnetic detection systems often result in a large number of false alarms due to the inability to effectively distinguish between a local geomagnetic anomaly in the background field and a target magnetic anomaly. To address this problem, this paper proposes a matching detection method for the magnetic anomaly of underwater targets. This method is based on the measured data of the magnetic anomaly in the sea area, and the geomagnetic reference map of the area is generated by interpolation of the Kriging method; then, the background field signal extracted from the geomagnetic reference map and the real-time signal acquired by detection are matched by the similarity metric algorithm; finally, the target detection is realized by using the feature fusion-isolation forest algorithm. Compared with the conventional detection methods, such as time–frequency analysis, the detection rate is improved by nearly 15% and the false alarm rate is reduced by about 40%, indicating that matching detection can effectively filter out the magnetic anomaly in the background field, reduce the false alarm, and improve the detection rate in the real geomagnetic environment, which has certain application value. [ABSTRACT FROM AUTHOR]

Seagrasses play an important role in coastal ecosystems and serve as important marine carbon stores. Acoustic monitoring techniques exploit the sensitivity of underwater sound to bubbles, which are produced as a byproduct of photosynthesis and present within the seagrass tissue. To make accurate assessments of seagrass biomass and productivity, a model is needed to describe acoustic propagation through the seagrass meadow that includes the effects of gas contained within the seagrass leaves. For this purpose, a new seagrass leaf model is described for Thalassia testudinum that consists of a comparatively rigid epidermis that composes the outer shell of the leaf and comparatively compliant aerenchyma that surrounds the gas channels on the interior of the leaf. With the bulk modulus and density of the seagrass tissue determined by previous work, this study focused on characterizing the shear moduli of the epidermis and aerenchyma. These properties were determined through a combination of dynamic mechanical analysis and acoustic resonator measurements coupled with microscopic imagery and finite element modeling. The shear moduli varied as a function of length along the leaves with values of 100 and 1.8 MPa at the basal end and 900 and 3.7 MPa at the apical end for the epidermis and aerenchyma, respectively. [ABSTRACT FROM AUTHOR]

The underwater sound absorption technique in low-frequency and broadband has far-reaching prospects since it is essential for noise reduction of deep-sea operation requirements and evading advanced underwater target detection. Here, we propose an underwater sound-absorbing composite lattice with low-frequency and ultra-broadband characteristics. The composite lattice is constructed by regular spatially stacking cells with different sizes of metallic core spheres. All the core spheres are coated with silicon rubbers, and cells are embedded in the rubber matrix. In the composite lattice stereostructure, the lattice cells convert incident longitudinal waves into transverse waves through multiple local resonance coupling and multiple scattering. The energy is localized and dissipated in the composite lattice. We analyze the relationship among the corresponding absorption spectrums, the displacement clouds, and the resonance modes of lattice cells. Then, we construct a composite lattice and realize low-frequency broadband absorption from 693 to 1106 Hz with absorptance above 0.8. Further, our investigation demonstrates that the absorption bandwidth can be extended to ultra-broadband from 1077 to 10 000 Hz, where the thickness of the composite lattice is λ / 17.05. The proposed composite lattice provides a practical approach to designing ultrathin low-frequency and ultra-broadband acoustic absorption coating for underwater noise suppression. [ABSTRACT FROM AUTHOR]

Underwater sound propagation is primarily driven by a nonlinear forward model relating variability of the ocean sound speed profile (SSP) to the acoustic observations (e.g., eigenray arrival times). Ocean acoustic tomography (OAT) methods aim at reconstructing SSP variations (with respect to a reference environment) from changes of the acoustic measurements between multiple source-receiver pairs. This article investigates the performance of three different OAT methods: (1) model-based methods (i.e., classical ray-based OAT using a linearized forward model), (2) data-driven methods (such as deep learning) to directly learn the inverse model, and (3) a hybrid solution [i.e., the neural adjoint (NA) method], which combines deep learning of the forward model with a standard recursive optimization to estimate SSPs. Additionally, synthetic SSPs were generated to augment the variability of the training set. These methods were tested with modeled ray arrivals calculated for a downward refracting environment with mild fluctuations of the thermocline. Idealized towed and fixed source configurations are considered. Results indicate that merging data-driven and model-based methods can benefit OAT predictions depending on the selected sensing configurations and actual ray coverage of the water column. But ultimately, the robustness of OAT predictions depends on the dynamics of the SSP variations. [ABSTRACT FROM AUTHOR]