Changes In Sound Speed Research Articles

On the accuracy of distance estimates by propagation time of sound signals on the arctic shelf

As part of numerical modeling, estimates are made of the accuracy of determining the distance between underwater sources and sound receivers located at a distance of several kilometers from each other in the Kara Sea in the autumn. It is assumed that the main source of possible errors in determining the distance is the lack of accurate data on the vertical profile of the sound speed along the propagation path of acoustic signals. Data from September and November were analyzed, in the interval between which significant changes in the profile take place, when the vertical gradient of sound speed changes from negative to positive values. Characteristic values of sound speed variations were obtained by statistical processing of hydrological data taken from the World Ocean Database. The results obtained are important for analyzing the capabilities of underwater acoustic navigation.

Imaging of ventilation and lung injury with low-frequency tomographic ultrasound.

Mechanical ventilation in the intensive care unit (ICU) is a life-saving technique for patients with acute respiratory failure, but is also associated with a high incidence of complications in the injured lung. Currently, there is no widely used monitoring technique to guide the ventilator setting to facilitate a precision medicine approach or to provide a real-time alert for developing adverse pulmonary conditions. Conventional ultrasound has been used as a thoracic bedside technology, but the lack of signal penetration into lung tissue results in images that often contain more information in their artifacts than in the images themselves. Perhaps the greatest obstacle to using traditional ultrasound in the ICU is the need for highly skilled technicians to perform the data collection. In contrast, low-frequency ultrasound (50-500 kHz) has been shown to penetrate the lung, and can detect air trapping in patients with chronic obstructive pulmonary disease (COPD). Here, we present a method of collecting low-frequency ultrasound computed tomographic (USCT) data in vivo on a mechanically ventilated porcine model and computing tomographic reconstructions of airflow during tidal breathing and induced lung injuries. We evaluate the ability of the novel low-frequency USCT system to image regional changes in sound speed in the thorax due to changes in airflow during tidal breathing and induced lung injuries. This represents the first study of low-frequency tomographic ultrasound imaging in vivo and the first to produce tomographic images of ventilatory changes invivo. USCT and computed tomography (CT) scan data were collected alternately on a mechanically ventilated Landrace pig weighing approximately 75 kg during tidal breathing, induced pneumothorax, atelectasis, and pleural effusion. The pneumothorax was induced by injecting air through a 5 mm thick intrathoracic tube inserted in the 8th posterior intercostal space. After removing the air, atelectasis was induced by ventilating the animal with a high concentration of oxygen and low tidal volumes. The pleural effusion was induced by injecting a saline solution through the tube. The USCT data were collected at 125 kHz using the USCT low-frequency ultrasound tomography (LUFT) system on a transducer belt placed around the animal's thorax. Tomographic reconstructions were computed from the USCT data using a regularized refraction-corrected Gauss-Newton-based time-of-flight reconstructionalgorithm. Cyclic changes in computed lung area during tidal breathing were demonstrated to agree with the respiratory rate on the mechanical ventilator. Reconstructed images computed at time steps during the procedure demonstrate regional changes consistent with what would be expected during the induced lung injury. No ground truth was available for images during the procedures since CT scans could only be taken before and after each established lunginjury. In this work, we have demonstrated in the first in vivo study using a mechanically ventilated porcine animal model that low-frequency ultrasound tomography has the ability to image regional changes in sound speed in the thorax corresponding to changes in airflow during tidal breathing and induced lung injury. The results show promise for using low-frequency USCT as a bedside imaging technique in the future for patients with acute respiratory distresssyndrome.

Experimental and numerical evaluation of the influence of voids on sound absorption behaviors of 3D printed continuous flax fiber reinforced PLA composites

This study aims to quantitatively analyze the effects of voids on sound absorption properties of 3D printed continuous flax fiber reinforced PLA composites (CFFRCs). Three kinds of flax yarns with different linear density were employed to prepare CFFRCs via 3D printing technology. The sound absorption performances of these composites were measured using the impedance tube based on the two-microphone transfer function method. The microstructure morphologies including cross-sections of flax yarns, voids shape and distributions of the composites were observed via ultra-depth microscope and micro-computed tomography to reconstruct the exact structures in simulation. Mercury intrusion porosimetry was applied to measure the voids dimensions of CFFRCs. The influence of voids on sound absorption mechanisms of CFFRCs were revealed based on thermoviscous acoustics theory by conducting the simulation in COMSOL software. The experimental results demonstrated that CFFRCs exhibited excellent sound absorption coefficients (close to 1) within the frequency range of 150–350 Hz and 350–550 Hz, resulting from the voids inside and between the flax yarns respectively. With the increase of linear density (diameter of the yarn), the contents of voids inside and between the flax yarns both increased. The dimensions of voids inside the flax yarns improved while those between flax yarns remained unchanged. The existence of the voids between the flax yarns resulted in a decrease in the sound absorption coefficient of CFFRCs, while more voids inside flax yarns led to the increase of the sound absorption frequency. Numerical results indicated that voids between the flax yarns contributed to a more uniform change in sound speed, reducing sound absorption performance. Whereas, voids inside the flax yarns could improve viscous friction of soundwaves due to narrow structures, enhancing sound absorption capabilities. This study is anticipated to provide a guidance for the design of integration of structure and function of 3D printed CFFRCs.

GNSS-A Network Solution with Zenith Acoustic Delay Estimation

The ocean sound speed changes drastically with time and space. It is almost impossible to achieve centimeter-level-precision Global Navigation Satellite System (GNSS)-Acoustic (GNSS-A) positioning without regarding spatio-temporal variations of sound speed. Inspired by the atmospheric delay estimation, we define zenith acoustic delay (ZAD) as the zenith-direction ranging error sourced by the sound speed variations, and then it is decomposed into one temporal component and two horizontal components for the sound speed variations in time and space, respectively. We propose a network solution with the three ZAD components of each seafloor geodetic point as common parameters to be estimated, and then present a piece-wise estimation to characterize their time-varying nature. To remedy the ray bending effect this study is implemented in the context of the ray tracing algorithm based on a reference sound speed profile (SSP). Experimental tests show that the proposed network solution improves ZAD estimation and results in a better position determination as compared to the single-point positioning (SPP) solution. The proposed network solution for a single campaign can achieve a horizontal positioning precision better than 5 cm (1-sigma) for the seafloor geodetic array centroid. The temporal variation of ZAD is up to one meter while the horizontal variations vary within a few decimeters in the time domain and show an azimuthal asymmetry in space.

Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to-Aberration Approach.

One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which disturbs the transmitted waves and prevents coherent summation of echo signals. Obtaining non-aberrated ground truths in real-world scenarios can be extremely challenging, if not impossible. This challenge hinders the performance of deep learning-based techniques due to the domain shift between simulated and experimental data. Here, for the first time, we propose a deep learning-based method that does not require ground truth to correct the phase aberration problem and, as such, can be directly trained on real data. We train a network wherein both the input and target output are randomly aberrated radio frequency (RF) data. Moreover, we demonstrate that a conventional loss function such as mean square error is inadequate for training such a network to achieve optimal performance. Instead, we propose an adaptive mixed loss function that employs both B-mode and RF data, resulting in more efficient convergence and enhanced performance. Finally, we publicly release our dataset, comprising over 180,000 aberrated single plane-wave images (RF data), wherein phase aberrations are modeled as near-field phase screens. Although not utilized in the proposed method, each aberrated image is paired with its corresponding aberration profile and the non-aberrated version, aiming to mitigate the data scarcity problem in developing deep learning-based techniques for phase aberration correction. Source code and trained model are also available along with the dataset at http://code.sonography.ai/main-aaa.

Low frequency inversion method based on multi-layer holizontal variation shallow seafloor model

Sound propagation in shallow water is significantly influenced by geoacoustic properties. Estimating these geoacoustic parameters is essential for sound field analysis and sonar performance assessment. As a common practice, the seafloor is often treated as a single-layer or two-layer range-independent geoacoustic model to reduce the number of involved parameters. However, acoustic parameters inverted through these two geoacoustic models are typically limited in their applicability to a specific frequency range, thus posing challenges when applied across a broader frequency range. A range-dependent multi-layer geoacoustic model based on experimental measurements obtained with a sub-bottom profiler is proposed in this study. The inversion scheme combines three inversion methods to estimate geoacoustic parameters, considering the different sensitivities of geoacoustic parameters to different physical parameters within the acoustic field. Firstly, modal dispersion is used to invert the geoacoustic parameters of each layer, with the dispersion curve obtained through warping transform and the Wigner-Ville distribution. After that, both the localization using matched field processing and the dispersion curve fitting demonstrate the effectiveness of the inversion results for each layer, although the peak of the probability distribution of sound speed in the first layer is broader than in others. Secondly, matched field processing is employed to invert the geoacoustic parameters of the first layer. This method is based on the theory that as frequency increases, the depth of sound rays penetrating the seabed decreases, revealing changes in the first layer's sound speed with the seabed depth. Lastly, bottom attenuation coefficients at different frequencies are inverted by the transmission loss (TL), and a fitting relationship between the attenuation coefficient and the frequency is derived. The inversion results obtained by using the range-dependent multi-layer geoacoustic model are compared with results estimated by the single-layer geoacoustic model. The findings indicate that the transmission loss (TL) error from the range-dependent multi-layer geoacoustic model in this study is smaller than that from the single-layer geoacoustic model, especially in the lower frequency band. The range-dependent multi-layer geoacoustic model proves to be suitable for a broader frequency range, providing better precision in explaining various acoustic phenomena.

Sensitivity of phase difference between short-range acoustic multipaths to changes in sound speed and source depth

Ocean acoustic tomography often relies on precise clocks and knowledge of the range between acoustic instruments to estimate ocean-driven sound speed changes. In this study, we explore an alternative method utilizing the difference in the carrier phase between two broadband pulse arrivals to estimate small-scale changes in source depth and sound speed. By leveraging acoustic multipathing, this phase difference approach obviates the need to know the acoustic propagation's precise range and absolute travel time. Observations from a mid-frequency (1–10 kHz) acoustic experiment at short ranges (2–3 km) demonstrate the sensitivity of the difference in the 4 kHz carrier phase between two arrivals to changes in both source depth and sound speed. The difference in the arrival phase is modeled using measurements of the time-varying source depth and sound speed. The comparison between the modeled and observed arrival phase differences reveals a significant agreement, supporting the potential of using phase difference as a reliable estimator for perturbations in either source depth or sound speed for short-range acoustic propagation.

Extraction and analysis of three-dimensional sound scattering characteristics by body-generated internal waves

The motion of an object submerged in a stratified fluid generates surface wakes, and simultaneously induces internal waves at the interface where there is a change in sound speed, known as the thermocline. As a result, spectral-temporal fluctuations occur in both the surface height and the distribution of sound velocity. While surface wakes primarily contribute to geometric acoustic scattering, the internal waves generated by the underwater object's motion can have diverse effects on sound propagation, leading to a prolonged acoustic impact that may have practical applications in underwater acoustic detection. This paper investigates the impact of body-generated internal waves on underwater acoustic propagation through the establishment of an “unfrozen field,” range-dependent model using the approximated Kelvin wake theory. The model allows numerical simulations to demonstrate the spatial-temporal coherence, time-frequency modulation and directional characteristics of the three-dimensional sound field scattered by the body-generated internal wave. By analyzing the influences of thermocline depth, target motion velocity and source depth, the results presented in this study indicate that the long-range acoustic propagation, modulated by the body-generated internal waves, can provide additional information for detecting moving targets.

Underwater Wireless Sensor Networks with RSSI-Based Advanced Efficiency-Driven Localization and Unprecedented Accuracy.

Deep-sea object localization by underwater acoustic sensor networks is a current research topic in the field of underwater communication and navigation. To find a deep-sea object using underwater wireless sensor networks (UWSNs), the sensors must first detect the signals sent by the object. The sensor readings are then used to approximate the object's position. A lot of parameters influence localization accuracy, including the number and location of sensors, the quality of received signals, and the algorithm used for localization. To determine position, the angle of arrival (AOA), time difference of arrival (TDoA), and received signal strength indicator (RSSI) are used. The UWSN requires precise and efficient localization algorithms because of the changing underwater environment. Time and position are required for sensor data, especially if the sensor is aware of its surroundings. This study describes a critical localization strategy for accomplishing this goal. Using beacon nodes, arrival distance validates sensor localization. We account for the fact that sensor nodes are not in perfect temporal sync and that sound speed changes based on the medium (water, air, etc.) in this section. Our simulations show that our system can achieve high localization accuracy by accounting for temporal synchronisation, measuring mean localization errors, and forecasting their variation. The suggested system localization has a lower mean estimation error (MEE) while using RSSI. This suggests that measurements based on RSSI provide more precision and accuracy during localization.

Numerical and experimental investigation of many-objective optimization for efficient temperature and velocity fields reconstruction via acoustic tomography

Accurate and high-quality measurement of temperature and velocity fields is important in combustion and flow diagnosis, especially for the control of boiler operations and optimization of combustion processes. Nonlinear acoustic tomography (NAT) is an appealing approach to simultaneously monitor temperature and velocity fields by observing the changes in sound speed they induce. However, the inherent ill-posedness of the tomographic inverse problem and the lack of a priori information may lead to poor robustness, low precision, and the presence of artifacts. On the other hand, the inclusion of a priori information, such as smoothness and box constraints, may require the use of hyperparameters that hinder quasi real-time reconstruction and may degrade performance in actual applications. In this study, we aim to ensure quasi real-time reconstruction and alleviate the ill-posedness of the NAT problem by eliminating the regularization parameters and transforming the inverse problem into a many-objective optimization problem with four objectives. The knee point-driven evolutionary algorithm with improved environmental selection strategy (KEA-IES) is proposed to simultaneously reconstruct the arbitrary inhomogeneous temperature and aerodynamic fields in a furnace. Apart from the investigation of the performance of KEA-IES and the influence of various factors, including measurement noise, function evaluation number, population size, and functional norms, on the quality of the reconstruction, an experimental AT system with independent 16 T/R channels is developed to evaluate the proposed method. The results show that combustion flame temperature and velocity fields can be monitored simultaneously by using the proposed KEA-IES with more accuracy, less consumed time, and better noise immunity compared with the state-of-the-art algorithms. The proposed method can provide valuable guidance in the development of a non-intrusive real-time pyrometry and velocimetry system, particularly for applications with large velocity fields and temperature gradients. Furthermore, its capability in complex combustion and flow diagnosis will offer benefits in terms of energy conservation, emission reduction, boiler operations supervision, and combustion process optimization.

Dynamic characterization of off the shelf polymer composites printed with fused deposition modeling

Fused deposition modeling (FDM) is the most common and cost effective form of additive manufacturing (AM). Due to the ubiquity of the approach, a range of off the shelf composite materials have been developed by companies, often with the goal of improving the printed part's physical appearance or increasing or decreasing the weight of the part. These composites typically have a base material of a standard FDM printed polymer, with additives such as metal particulates or lightweight filler added. This study will examine the dynamic properties of a set of off the shelf materials to characterize acoustic sound speed, complex elastic moduli, and loss. All of the materials in this study have a base material of polylactic acid (PLA) making it possible to easily print them into multi-material structures. The filler materials showed minimal impact on some viscoelastic properties but resulted in significant changes in acoustic sound speed. Characterization of this type is a critical component in development of an expanded database of material properties for use in design.

Performance of single empirical orthogonal function regression method in global sound speed profile inversion and sound field prediction

The sound speed profile (SSP) reflects the change in sound speed from the surface to the bottom of the seawater, which will have an important influence on underwater acoustic detection and communication. Depending on the inversion of sea surface data sets measured by satellite to obtain near-real-time and high-precision SSPs has become a research hotspot. In this paper, based on the Argo data and the sea surface data sets, we use the single empirical orthogonal function regression (sEOF-r) method to inverse the global SSPs and evaluate the performance of this method. There are also differences in the performance of inversed results at different sites and in different months at the global scale of the ocean. The eddy kinetic energy (EKE) affects the accuracy of inversion, we propose to add the EKE into the inversion formula at the same time to further optimize the inversed results and improve the accuracy, the global average inversion error after optimization reduces by 20%. Finally, we verify the effectiveness of the optimized method from the perspective of sound field prediction. In most cases, the correlation coefficient of the transmission loss (TL) calculated through the inversion SSP and Argo-SSP exceeds 0.7 and the error is controlled below 6 dB, which will have important implications for the actual sound field prediction and hydroacoustic communication.

Ex vivo evaluation of the sensitivity of modified average speed of sound estimation method

The speed of sound (SoS), which is the propagation speed of longitudinal waves, is expected to be effective for the early detection and monitoring of diseases. Several methods that use handheld probes have been proposed to estimate the SoS. In this study, a modified average SoS estimation method, referred to as the improved focusing method, is proposed to increase the accuracy of average SoS estimation. In the proposed method, a plane wave was transmitted, and the center-element position-dependent variations in the SoS estimation were reduced. Ex vivo experiments were conducted using chicken liver to evaluate the applicability and sensitivity of the proposed method to actual tissues. The livers were subjected to continuous temperature changes to induce changes in the SoS. The results suggest that the improved focusing method measures the average SoS accurately as well as small SoS changes of approximately 1.5 m·s−1·°C−1.

A sonic black hole structure with perforated boundary for slow wave generation

A Sonic Black Hole (SBH) in a retarding duct structure incorporates two indispensable physical processes, i.e., wave energy focalization and dissipation, to entail slow-sound effect and broadband sound absorption. Original SBH design, however, involves a large number of inner rings inside the duct to produce the required impedance changes. In this study, a SBH configuration with perforated boundary (SBH-PB) is examined, in which perforated acoustic boundaries are used to achieve enhanced SBH effects. Upon a dedicated treatment of the perforated boundary (PB) with the backing cavity, the transfer matrix method (TMM) is adopted to analyze the acoustic characteristics of the SBH-PB and to explore the underlying physical mechanisms. The adoption of the PB is shown to bring about threefold benefits: increased accuracy of the TMM modeling owing to the weakened coupling among the backing cavities in the SBH-PB, enhanced sound absorption through micro-perforations, and the realization of SBH effects with a reduced number of inner rings. To visualize the slow-sound effect, the change of sound speed is examined through transient simulations using finite element method by capturing the wavefront propagation inside the duct. Finally, for the first time, an acoustic duct system replicating the transient simulations is developed to experimentally demonstrate the slow-wave phenomenon in the time domain. The proposed structure holds promises for sound wave manipulation and the development of acoustic noise control devices.

Assessment and Non-Destructive Evaluation of the Influence of Residual Solvent on a Two-Part Epoxy-Based Adhesive Using Ultrasonics

Polymers are increasingly being used in higher demanding applications due to their ability to tailor the properties of structures while allowing for a weight and cost reduction. Solvents play an important role in the manufacture of polymeric structures since they allow for a reduction in the polymer’s viscosity or assist with the dispersion of fillers into the polymer matrix. However, the incorrect removal of the solvent affects both the physical and chemical properties of polymeric materials. The presence of residual solvent can also negatively affect the curing kinetics and the final quality of polymers. Destructive testing is mainly performed to characterize the properties of these materials. However, this type of testing involves using lab-type equipment that cannot be taken in-field to perform in situ testing and requires a specific sample preparation. Here, a method is presented to non-destructively evaluate the curing process and final viscoelastic properties of polymeric materials using ultrasonics. In this study, changes in longitudinal sound speed were detected during the curing of an aerospace epoxy adhesive as a result of variations in polymer chemistry. To simulate the presence of residual solvent, samples containing different weight percentages of isopropyl alcohol were manufactured and tested using ultrasonics. Thermogravimetric analysis was used to show changes in the decomposition of the adhesive due to the presence of IPA within the polymer structure. Adding 2, 4, and 6 wt.% of IPA decreased the adhesive’s lap shear strength by 40, 58, and 71%, respectively. Ultrasonics were used to show how the solvent influenced the curing process and the final sound speed of the adhesive. Young’s modulus and Poisson’s ratio were determined using both the longitudinal and shear sound speeds of the adhesive. Using ultrasonics has the potential to non-invasively characterize the quality of polymers in both an in-field and manufacturing settings, ensuring their reliability during use in demanding applications.

Localization of an acoustic autonomous underwater vehicle using multi-channel back-propagation methods

Autonomous underwater vehicles (AUVs) are extremely useful tools for studying the acoustics of complex ocean environments due to their ability to detect environmental changes with greater spatial resolution than fixed moorings. During the New England Shelf Break Acoustics (NESBA) experiments in May 2021, an AUV system was deployed to collect acoustic data for investigating the local biological, physical, and geological oceanography. This acoustic AUV system was comprised of a modified REMUS 600 vehicle, a hull-mounted 3.5 kHz transducer, and a towed multi-channel hydrophone array. Along mission profiles where the AUV is fully submerged but too shallow for bottom-lock navigation, one challenge is accurate localization of the AUV. Localization was performed in post-processing using multi-channel back-propagation methods applied to AUV source signals received at mooring hydrophones in the NESBA network as well as ship-towed sound source signals received at the AUV-towed array. Uncertainty in the localization estimates due to spatiotemporal sound speed changes was investigated, and hydrophone mooring tilt angle was determined by minimizing the localization uncertainty. Following localization, this AUV acoustic data was used to investigate local seafloor sub-bottom properties and the acoustic effects of biological scattering layers and varying physical oceanography. [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.

Quantitative characterization of the ultrasound thermal strains in tissue mimicking phantoms with different oil concentrations

Ultrasound thermal strain imaging (US-TSI) has been known for the capability of tissue characterization according to distinct sound speed change in different tissues when temperature increases. US-TSI for detecting lipids in atherosclerosis plaques and fatty livers has previously been reported while some practical challenges were not fully addressed, especially due to physiological motions. To overcome such limitation, we recently developed an ultrasound transducer that combines an acoustic heating array and an imaging array to achieve US-TSI with heating performed in a region of approximately 10 mm by 5 mm by 2 mm within a very short time period of about 50 ms compared both cardiac and breathing motions. To characterize the new US-TSI probe, a thorough benchtop investigation was performed on the relationship among the threekey variables for TSI: thermal strain, temperature increase, and lipid concentration. In the experiments, homogeneous oil-in-gelatin phantoms of different oil concentrations were fabricated to simulate different lipid-plaque concentrations. Temperature curves were recorded by a thermal couple with millisecond-level time constant. Thermal strains were computed by developed US-TSI signal processing procedures. The results build a tissue-temperature-strain model and calibrate the new US-TSI probe for in vivo atherosclerosis plaque characterization.

Multimodal assessment of non-alcoholic fatty liver disease with transmission-reflection optoacoustic ultrasound.

Non-alcoholic fatty liver disease (NAFLD) is an umbrella term referring to a group of conditions associated to fat deposition and damage of liver tissue. Early detection of fat accumulation is essential to avoid progression of NAFLD to serious pathological stages such as liver cirrhosis and hepatocellular carcinoma. Methods: We exploited the unique capabilities of transmission-reflection optoacoustic ultrasound (TROPUS), which combines the advantages of optical and acoustic contrasts, for an early-stage multi-parametric assessment of NAFLD in mice. Results: The multispectral optoacoustic imaging allowed for spectroscopic differentiation of lipid content, as well as the bio-distributions of oxygenated and deoxygenated hemoglobin in liver tissues in vivo. The pulse-echo (reflection) ultrasound (US) imaging further provided a valuable anatomical reference whilst transmission US facilitated the mapping of speed of sound changes in lipid-rich regions, which was consistent with the presence of macrovesicular hepatic steatosis in the NAFLD livers examined with ex vivo histological staining. Conclusion: The proposed multimodal approach facilitates quantification of liver abnormalities at early stages using a variety of optical and acoustic contrasts, laying the ground for translating the TROPUS approach toward diagnosis and monitoring NAFLD in patients.

Sound propagation measurements using an autonomous underwater vehicle acoustic array in the New England shelf break acoustics network

The New England shelf break is a highly dynamic region, which experiences complex spatial and temporal water-column variations due to interactions with warm core rings originating from the gulf stream. This widely varying ocean environment leads to changes in sound speed and acoustic propagation. Acoustic payload-equipped autonomous underwater vehicles (AUVs) are advantageous for sound propagation measurements in such environments due to their ability to detect changes with greater spatial resolution compared to fixed moorings. An AUV-towed acoustic array was tested and deployed in the New England Shelf Break Acoustics (NESBA) experiment in May 2021. The acoustic AUV system was comprised of a modified REMUS 600 vehicle, a hull-mounted 3.5 kHz transducer, and a towed multi-channel linear hydrophone array. The AUV sound source was tested at the Dodge Pond Naval Facility to characterize the effect of AUV body resonance, and the resulting calibration was incorporated into the data processing. Propagation paths between the AUV, acoustic moorings, and a ship-towed sound source were studied to investigate the acoustic effects of varying physical oceanographic conditions and biological scattering layers. These measurements also enabled investigation of the local seabed conditions and sub-bottom layering structure. [Work supported by the Office of Naval Research.]