Sound Speed Variations Research Articles

Observations and simulations of caustic formation due to oceanographic fine structure.

An at-sea experiment in deep water was conducted to explore the impact of small-scale sound-speed variability on mid-frequency (1-10 kHz) acoustic propagation. Short-range (1-5 km) acoustic transmissions were sent through the upper ocean (0-200 m) while oceanographic instruments simultaneously measured the ocean environment within 2 km of the single upper turning points of the acoustic transmissions. During these transmissions, acoustic receptions over a 7.875 m vertical line array show closely spaced, sometimes interfering arrivals. Ray and full-wave simulations of the transmissions using nearby sound-speed profiles are compared deterministically to the received acoustic signals. The sensitivity of the acoustic arrivals to the vertical scales of ocean sound speed is tested by comparing the observed and simulated arrival intensity where the sound-speed profile used by the simulation is smoothed to varying scales. Observations and modeling both suggest that vertical fine-scale structures (1-10 m) embedded in the sound-speed profile have strong second derivatives which allow for the formation of acoustic caustics as well as potentially interfering acoustic propagation multipaths.

Investigating the reliable acoustic path properties in a global scale

Leveraging the benefits of low transmission loss and high signal-to-noise ratio, the reliable acoustic path (RAP) has been extensively employed in various underwater applications. In this study, we investigate RAP properties on a global scale. Acoustic simulations were conducted using global grids with a 0.25° × 0.25° spatial resolution, revealing that RAP range is positively correlated with ocean depth. Contrary to the prevailing belief that RAP properties are relatively unaffected by sound speed variations, our findings indicate that sound speed profiles (SSPs) play a crucial role in determining RAP properties by altering the RAP from 15 km to 50 km at a constant ocean depth of 4000 m. Additionally, the receiver angle can vary by nearly 5 km at the same source location due to SSP variations. Consequently, utilizing highly accurate SSPs can enhance the performance of underwater localization or communication systems that rely on RAP.

Acoustic ducting by shelf water streamers at the New England shelfbreak.

Greater sound speed variability has been observed at the New England shelfbreak due to a greater influence from the Gulf Stream with increased meander amplitudes and frequency of Warm Core Ring (WCR) generation. Consequently, underwater sound propagation in the area also becomes more variable. This paper presents field observations of an acoustic near-surface ducting condition induced by shelf water streamers that are related to WCRs. The field observations also reveal the subsequent disappearance of the streamer duct due to the passage of a WCR filament. These two water column conditions are investigated with sound propagation measurements and numerical simulations.

Observations of the space/time scales of Beaufort sea acoustic duct variability and their impact on transmission loss via the mode interaction parameter.

The Beaufort duct (BD) is a subsurface sound channel in the western Arctic Ocean formed by cold Pacific Winter Water (PWW) sandwiched between warmer Pacific Summer Water (PSW) and Atlantic Water (AW). Sound waves can be trapped in this duct and travel long distances without experiencing lossy surface/ice interactions. This study analyzes BD vertical and temporal variability using moored oceanographic measurements from two yearlong acoustic transmission experiments (2016-2017 and 2019-2020). The focus is on BD normal mode propagation through observed ocean features, such as eddies and spicy intrusions, where direct numerical simulations and the mode interaction parameter (MIP) are used to quantify ducted mode coupling strength. The observations show strong PSW sound speed variability, weak variability in the PWW, and moderate variability in the AW, with typical time scales from days to weeks. For several hundreds Hertz propagation, the BD modes are relatively stable, except for rare episodes of strong sound speed perturbations. The MIP identifies a resonance condition such that the likelihood of coupling is greatest when there is significant sound speed variability in the horizontal wave number band 1/11<kh<1/5 km-1. MITgcm ocean model results are used to estimate sound speed fluctuations in this resonance regime.

Glitches in solar-like oscillating F-type stars

Context. The transition between convective and radiative stellar regions is still not fully understood. This currently leads to a poor modelling of the transport of energy and chemical elements in the vicinity of these regions. The sharp variations in sound speed located in these transition regions give rise to a signature in specific seismic indicators, opening the possibility to constrain the physics of convection to radiation transition. Among those seismic indicators, the ratios of the small to large frequency separation for l = 0 and 1 modes (r010) were shown to be particularly efficient to probe these transition regions. Interestingly, in the Kepler Legacy F-type stars, the oscillatory signatures left in the r010 ratios by the sharp sound-speed variation have unexpected large amplitudes that still need to be explained. Aims. We analyse the r010 ratios of stellar models of solar-like oscillating F-type stars in order to investigate the origin of the observed large amplitude signatures of the r010 ratios. Methods. We tested different possibilities that may be at the origin of the large amplitude signatures using internal structures of stellar models. We then derived an analytical expression of the signature, in particular, of the amplitude of variation, that we tested against stellar models. Results. We show that the signature of the bottom of the convective envelope is amplified in the ratios r010 by the frequency dependence of the amplitude compared to the signal seen in the frequencies themselves or the second differences. We also find that with precise enough data, a smoother transition between the adiabatic and radiative temperature gradients could be distinguished from a fully adiabatic region. Furthermore, we find that among the different options of physical input investigated here, large amplitude signatures can only be obtained when convective penetration of the surface convective zone into the underlying radiative region is taken into account. In this case and even for amplitudes as large as those observed in F-type stars, the oscillating signature in the r01 ratios can only be detected when the convective envelope is deep enough (i.e. at the end of the main sequence). Assuming that the origin of the large amplitude glitch signal is due to penetrative convection (PC), we find that the PC must extend downward the convective to radiative transition significantly (about 1 − 2Hp) in order to reproduce the large amplitudes observed for the ratios of F-type stars. This deep extension of the convective envelope causes doubt that the origin of the large amplitudes is due to PC as it is modelled here or implies that current stellar modelling (without PC) leads to an underestimation of the size of convective envelopes. In any case, studying the glitch signatures of a large number of oscillating F-type stars opens the possibility to constrain the physics of the stellar interior in these regions.

Effect of oceanography on broadband acoustic wave propagation in a range dependent shallow water environment

To investigate the effects of oceanographic variability on broadband acoustic wave propagation in shallow water environments, two experiments were carried out on the New England continental shelf region in 2017 and 2022, respectively. Towed sources were used to transmit chirp waveforms over the frequency ranges of 0.5—1.25 kHz and 1.5 – 4.0 kHz on the same acoustic tracks. The broadband acoustic transmissions were received by vertical acoustic arrays with multiple hydrophones. In 2017, the sound speed in the water column was isovelocity while in 2022 the presence of a duct at the depth of 20 m and upward refracting conditions reduced the interaction of acoustic transmissions with the seafloor compared to the experiment in 2017. Experimental observations show the importance of the water column on bottom interacting broadband waveforms causing challenges for the inversion algorithms. In this paper, we present acoustic and oceanographic results showing how the variability of sound speed could change the characteristics of the broadband transmission. Modeled results versus experimental data are discussed. [Work supported by ONR.]

Introducing sound speed variability in laboratory water tank

The variation of temperature in the ocean causes changes in sound propagation. To simulate the naturally occurring variability in an ocean environment, this project quantified the sound speed variation achievable in a laboratory water tank. The rectangular tank (1.2 m × 3.6 m with 0.5 m depth) has anechoic paneling that minimizes lateral reflections. In this experiment, temperature was measured from four different temperature sensors. The temperature was used to calculate the sound speed in the tank as a function of time while the water was cooled and heated. Sound speed values were compared from four different empirical equations. We found that while the temperature varies in time, the temperature is relatively uniform at different locations in the tank. In experiments involving three hours of heating and adding 100 pounds of ice, there was a 10-degree Celsius difference in temperature, corresponding to a 20 m/s difference in water sound speed. By adding an additional degree of variability to the tank measurements, a portion of the variability seen in the ocean can be replicated. This sound speed variability can then be used to test the robustness of machine learning algorithms.

Performance study of ocean acoustic tomography methods in the upper-ocean environment using autonomous platforms

Accurate knowledge of the spatial and temporal evolution of the three-dimensional ocean sound speed profile (SSP) is crucial for underwater source localization. Ocean acoustic tomography (OAT) methods aim at reconstructing SSPs variations based on acoustic measurements between multiple source-receiver pairs (e.g., eigenrays arrival times). This study investigates the estimation of range-dependent SSPs using a classical model-based OAT method (i.e., ray-based ocean acoustic tomography), for various configurations of source and receiver configurations using autonomous platforms in a highly-dynamic upper ocean environment. A regional oceanographic simulation of the De Soto Canyon circulation in the Gulf of Mexico is used to construct 3D sound speed variations spanning a month long which exhibits significant sub-mesoscale variability. Two main aspects affecting OAT performance in the presence of high 3D SSPs variability are investigated: (1) The influence of the input acoustic data (i.e., source-receivers configuration and platform motion, arrival-times accuracy...) and (2) the actual implementation of the OAT scheme (i.e., selection of complexity reduction basis, linearized forward model assumptions as well as the use of iterative solvers) on SSPs estimations errors. Practical implications for the design of OAT experiments in the dynamic upper ocean will be discussed. [Work supported by the Office of Naval Research.]

Climate-induced changes in temperature, salinity, and sound speed in the global ocean

Oceans play a significant role in climate change by absorbing the earth's excess heat and transporting heat from one location to another. Melting and reducing ice coverage, rising sea levels, ocean acidification, and changes in underwater sound propagation are a few impacts of global warming on oceans. Marine lives have been threatened by many of these alterations, such as interference of their communications and reduction of their habitable places, resulting in the ocean ecosystem imbalance. Ocean datasets containing temperature and salinity are necessary to measure the warming rates and places, access the magnitude and extent of the impacts, and consider mitigation policies. Data collected by traditional in situ measurement techniques are insufficient for this purpose because of the scarcity of the measurements in the vast ocean. Here, an idea to overcome the limitation is proposed by using machine learning to infer the ocean temperature and salinity from satellite-observed sea surface temperature and salinity data that are broadly available. Following the predicted temperature and salinity values, global warming indicators, such as ocean heat content and mixed layer depth, are examined. Also examined are the underwater sound speed variations.

Seabed classification with ResNet-18 using multi-channel ship noise spectrograms

Transiting cargo ships in the ocean generate noise that can be used to infer the effective seabed type below. Recently this has been demonstrated with a residual convolutional neural network trained on synthetic data that displays frequency and range-dependent transmission loss generated by a range-independent normal model and empirical source spectrum for ship noise. The generalizability of the trained model was tested on ship noise measured from the middle sensor of a 16-channel vertical line array near shipping lanes on the New England continental shelf. In contrast, this current work utilizes multiple sensors and seeks to determine the optimal combination of sensor data. It was discovered that including sensors near the seabed improved model performance. Best results were obtained when the model’s average sensor depth was 75%–80% of the water depth. The distance between sensors had no discernible effect on performance. Although the almost isovelocity sound speed profile used in this study indicated little difference between one-channel and two-channel model performance, future analyses will test the hypothesis that the use of multiple sensors will improve model performance for greater sound speed variation. [Work supported by the Office of Naval Research and the National Science Foundation REU program.]

Sound Speed Estimation for Distributed Aberration Correction in Laterally Varying Media.

Spatial variation in sound speed causes aberration in medical ultrasound imaging. Although our previous work has examined aberration correction in the presence of a spatially varying sound speed, practical implementations were limited to layered media due to the sound speed estimation process involved. Unfortunately, most models of layered media do not capture the lateral variations in sound speed that have the greatest aberrative effect on the image. Building upon a Fourier split-step migration technique from geophysics, this work introduces an iterative sound speed estimation and distributed aberration correction technique that can model and correct for aberrations resulting from laterally varying media. We first characterize our approach in simulations where the scattering in the media is known a-priori. Phantom and in-vivo experiments further demonstrate the capabilities of the iterative correction technique. As a result of the iterative correction scheme, point target resolution improves by up to a factor of 4 and lesion contrast improves by up to 10.0 dB in the phantom experiments presented.

Acoustic field fluctuation caused by source-generated internal waves and its detection method

The development of noise reduction and silencing technology has brought great difficulties to underwater target detection, and more target characteristics need further studying. When a submerged target travels through density-stratified environment, the fluid will oscillate behind the target owing to gravity and buoyancy and generate internal waves, which are often referred to as source-generated internal waves. These internal waves are difficult to eliminate, which can cause the sound speed profiles to fluctuate. Therefore, these internal waves are expected to be effective for detecting underwater target. In this paper, the fluctuations of the received sound passing through the internal waves produced by a moving sphere are investigated. A typical shallow stratified environment is set up, and internal wave fields generated by a sphere moving in many horizontal directions are simulated. According to the simulation results, these internal wave fields have a much wider range than the scenario of the target body. Based on the relationship between the amplitude of the internal wave and the variation of sound speed, range–dependent sound speed profiles are constructed, and model based on ray acoustics is used to analyze the aberration strength of passing sound fields. Results show that the strength aberration is inversely proportional to the target passing angle, and these characteristics can be covered by the background. Focusing on this problem, an extraction method based on principal component analysis with sliding window is then proposed. The uncorrelation between the disturbance of internal wave and background signal is utilized, and interference is suppressed by removing the component in No.1 principal component space, and retaining the No.2–No.&lt;i&gt;k&lt;/i&gt; subspace. Detection can be executed based on multi period received data from single hydrophone. A lake experiment is conducted to verify the performance. A detection scenario of single source and single receiver is established, and the AUV target crosses source–receiver line multiple times. The research results show that the detection scheme based on the acoustic aberration of source-generated internal wave has potential for underwater target detection, possessing the advantages of wide coverage and high robustness. Data on multi depths are processed to show that the detection performance is dependent on the depth of system. Since the acoustic strength variations are derived form local disturbance in channel, the proposed method may be affected by severe environment fluctuation, and further research is still needed.

Supervised Classification of Sound Speed Profiles via Dictionary Learning

Abstract The presence of internal waves (IWs) in the ocean alters the isotropic properties of sound speed profiles (SSPs) in the water column. Changes in the SSPs affect underwater acoustics since most of the energy is dissipated into the seabed due to the downward refraction of sound waves. In consequence, variations in the SSP must be considered when modeling acoustic propagation in the ocean. Empirical orthogonal functions (EOFs) are regularly employed to model and represent SSPs using a linear combination of basis functions that capture the sound speed variability. A different approach is to use dictionary learning to obtain a learned dictionary (LD) that generates a nonorthogonal set of basis functions (atoms) that generate a better sparse representation. In this paper, the performance of EOFs and LDs are evaluated for sparse representation of SSPs affected by the passing of IWs. In addition, an LD-based supervised framework is presented for SSP classification and is compared with classical learning models. The algorithms presented in this work are trained and tested on data collected from the Shallow Water Experiment 2006. Results show that LDs yield lower reconstruction error than EOFs when using the same number of bases. In addition, overcomplete LDs are demonstrated to be a robust method to classify SSPs during low, medium, and high IW activity, reporting accuracy that is comparable to and sometimes higher than that of standard supervised classification methods.

HearFire

Indoor conflagration causes a large number of casualties and property losses worldwide every year. Yet existing indoor fire detection systems either suffer from short sensing range (e.g., ≤ 0.5m using a thermometer), susceptible to interferences (e.g., smoke detector) or high computational and deployment overhead (e.g., cameras, Wi-Fi). This paper proposes HearFire, a cost-effective, easy-to-use and timely room-scale fire detection system via acoustic sensing. HearFire consists of a collocated commodity speaker and microphone pair, which remotely senses fire by emitting inaudible sound waves. Unlike existing works that use signal reflection effect to fulfill acoustic sensing tasks, HearFire leverages sound absorption and sound speed variations to sense the fire due to unique physical properties of flame. Through a deep analysis of sound transmission, HearFire effectively achieves room-scale sensing by correlating the relationship between the transmission signal length and sensing distance. The transmission frame is carefully selected to expand sensing range and balance a series of practical factors that impact the system's performance. We further design a simple yet effective approach to remove the environmental interference caused by signal reflection by conducting a deep investigation into channel differences between sound reflection and sound absorption. Specifically, sound reflection results in a much more stable pattern in terms of signal energy than sound absorption, which can be exploited to differentiate the channel measurements caused by fire from other interferences. Extensive experiments demonstrate that HireFire enables a maximum 7m sensing range and achieves timely fire detection in indoor environments with up to 99.2% accuracy under different experiment configurations.

Effect of Undersea Parameters on Reliability of Underwater Acoustic Sensor Network in Shallow Water

Underwater acoustic sensor networks have attained intensifying significance within the research communality, since they are enabling technology for wide range of applications. Typically, these networks establish connectivity (single or multi-hop) by a means of acoustic links. Acoustic communications pose several challenges due to transmission losses, fading, multipath, and effect of medium characteristics (depth, salinity, temperature and pH) on sound speed. The variation in sound speed affects the link formation, which may lead to link failures among sensor nodes. It seems to be crucial to incorporate a channel model that reflect on effect of medium and channel characteristics (absorption and transmission losses) in order to accomplish reliable communication among the links in an underwater network. In this work, an evaluation method for the two-terminal reliability of underwater sensor networks deployed in shallow water scenarios has been proposed. The methodology takes into account an acoustic channel model that distinguishes the effect of frequency and the aforementioned parameters on link formation. Two-terminal reliability analysis has been carried out by considering the effect of underwater media properties. The experimental outcomes specify that, reliability is reaches its maximum value when the temperature and salinity discrepancy with respect to depth are insignificant at lesser frequencies than that of upper frequencies.

FastICA Algorithm Applied on Black Sea Water-Level Ultrasound Measurements

The parameters influencing the sea level measured with ultrasonic devices that are analyzed in this paper are the air temperature, atmospheric pressure and wind speed. As these variations are independent to each other and to the sea level, they can be removed from the measured sea level by applying a filtering algorithm based on independent component analysis (FastICA), adapted and improved for this application. The sound speed increases with temperature, so an internal temperature sensor is required to compensate for the sound-speed variation. Though this may improve the measurement accuracy, it is not enough to achieve the best results because there is a discrepancy between the internal sensor and the actual environment temperature. For high accuracy measurements, an external temperature sensor is required. In our case, we imported temperature datasets from a weather station, along with other datasets regarding atmospheric pressure and wind speed. The use of these external datasets, along with an algorithm based on principal component analysis (PCA) for error removal and the filtering algorithm based on FastICA for environmental phenomena extraction, allows us to achieve more accurate values for the Black Sea level in Constanta (2017–2020), independent of external influences.

The refined resilient model for underwater acoustic positioning

The variation of sound speed is a major factor affecting the accuracy of the acoustic positioning underwater. A refined resilient model is constructed which includes temporal variations and horizontal variations on the basis of the simple resilient observation model which includes range bias and time bias parameters. The integrated estimation method and the stepwise estimation method were used to calculate the temporal and spatial variations of the sound speed using the GNSS-Acoustic (GNSS-A) measurements. The sound speed model was used in the long baseline (LBL) underwater acoustic positioning, and the position of the transducer calculated by acoustic ranges is compared with that provided by GNSS. The results show that, there are obvious temporal and spatial variations in the sound speed in different water area. The temporal variation of the sound speed is less than 0.8 m/s and the spatial variation is less than 0.15 m/s. The variation of sound speed under water not only shows obvious periodicity, but also presents negative gradient in the horizontal direction. When the coordinates of the transducer are calculated by using the sound speed model considering temporal and spatial variations constructed by the integrated estimation, the precision of the coordinates is improved by about 28%, compared with that calculated using the constant sound speed model. The 3D root mean square (RMS) of the LBL underwater acoustic positioning is about 0.73 m, and the RMS is less than 0.13 m in the vertical direction, when the coordinates of the ship bottom transducer are calculated within the area covered by five seafloor transponders. It indicates that the coordinate accuracy of the five seafloor transponders is high in the vertical direction.

Application of a chord transducer for ultrasonic detection and characterisation of defects in MDPE butt fusion joints

Butt fusion (BF) is the standard method for joining polyethylene (PE) pipes during gas and water pipeline construction. The joints require simple, inexpensive and effective non-destructive testing techniques. Ultrasonic inspection is the most suitable approach; however, joint geometry requires specific configuration of the acoustic beam. In this article, a custom-designed ultrasonic chord transducer optimised for a specific pipe diameter is described. It is demonstrated how variations of sound speed and attenuation in pipe material with temperature variations affects the operation of this type of transducer. A variety of common defects, including cold fusion, dust, dirt, grass contamination, voids, etc, are simulated inside the joint and used for technique development. Analysis of an A-scan produced in pitch-catch mode allows for the evaluation of joint quality and the classification of defect type.

Quantifying the influence of the vertical resolution in ocean circulation modeling on the acoustic propagation through mesoscale eddies

Accurate numerical simulations of underwater acoustic propagation in a dynamic ocean—and its associated uncertainty—require using realistic environmental parameters as inputs and especially a high-fidelity representation of the expected spatio-temporal variability of the ocean sound speed in the volume of interest. In areas characterized by strong temperature and salinity variations (e.g., associated with long-living mesoscale eddies in the Gulf of Mexico), the approximate simulation of the 3D sound-speed field and its variability requires predictive oceanographic models capable of resolving such variations. This study investigates the impact of vertical resolution focusing on how it shapes the representation of the 3D sound speed variability through a suite of simulations of the northern Gulf of Mexico performed with a regional ocean model run at submesoscale permitting horizontal resolution (0.5 km) using increasing vertical resolution from 30 to 200 terrain-following layers over a one-month simulation interval (as described in the companion paper presented by Touret et al.). Geo-acoustic parameters were matched to the existing sediment database. In selected areas influenced by mesoscale eddies, ray tracing is used to determine the significance of increased resolution on acoustic propagation as a function of the sensor configurations and the expected sound speed variability.

Broadband acoustic wave propagation in temporally variable range dependent shallow water environment

Broadband acoustic wave propagation in shallow water regions involves interactions with the sea surface, sea bottom, and the water column. The topic of shallow water acoustics in the presence of variable water column has been of interest in recent years. Experimental observations have shown the importance of the effects due to the boundaries and the sound speed profile in the water column. However, more work needs to be done to establish ground truth in numerical modeling for temporally variable water column in a range dependent environment. In this paper we examine the broadband propagation on the shelf as well as the range dependent shelf break regions to depict how temporal variability of sound speed could change the dispersion characteristics of the broadband signal. Comparison between modeled and experimental data are provided. [Work supported by ONR OA program.]