Session K04: Acoustics

Ocean acoustics and expanded equivalent-fluid methods

The effectiveness of sound propagation in the ocean means that acoustic energy provides an important tool as an environmental probe but also constitutes a potential environmental concern. Effective computational modeling plays an important role in both ocean acoustic tomography and the characterization of possible impacts. When there is significant acoustic interaction with the bottom, the model must incorporate a bottom treatment. This can be challenging if relatively long propagation ranges are of interest. Depending on the nature of the seafloor, shear waves in the bottom may be a contributor to acoustic losses in the water column. A physical treatment of this shear propagation is computationally demanding and often not necessary if it is solely the acoustic signal in the water column that is of interest. "Equivalent fluid" methods have been used extensively to model bottom reflection, often incorporating a complex number for the "density" parameter to easily incorporate this loss mechanism. Previous approaches in complex-density equivalent fluids typically examine the limit of low shear speed and low grazing angle. The method can be expanded to construct equivalent-fluid parameters for additional quantities in order to mimic the reflection coefficient of the actual elastic solid for the grazing angle interval of interest. Test cases involving near-source propagation over volcanic basalt and high grazing angle configurations will be presented. Refinements to the method will be addressed.   

A laboratory study of acoustic behaviors of bubbles caused by oil leakages

A laboratory study to simulate oil leakages was conducted under controlled conditions, such as pressures, flow rates, jet velocities, and crack sizes. Two types of oil leakages, a few bubble cases and the constant flow bubble cases, were tested to simulate oil seepages either from seafloors or from oil well and pipe-line breaches. Two gases, nitrogen and methane, were used for the investigation. The bubble sounds were recorded by hydrophones. It was found that (1) the resonant frequency decreased nonlinearly with the needle diameter and (2) the sound intensity in terms of the total energy increased with both the flow rate and jet velocity. For acoustic bubble modeling, we implemented the theory of bubble dynamics to analyze the bubble sounds. We considered (1) the dependence of the resonant frequency on the size of crack, and (2) the dependence of the sound intensity in terms of the total energy on the flow rate and jet velocity. Several correlations between the oil leakage properties and acoustic responses were established and interpreted. The outcome of the observations and modeling enhanced our understanding of the mechanisms of bubble-induced sounds and will be applied to guide the assessment of the features of oil.   

Speeds of sound in salt water at high salinities

The speeds of sound in salt water mixtures were measured over a range of salinities from 3% to 24%, which runs from 1x to 7x relative to the nominal value in ocean water. The measurements were made using an ultrasonic pulse-echo technique using the speed of sound in distilled water as a reference with timing offsets determined via cross-correlation. The results exhibited a trend consistent with published values with a speed increase of over 230 m/s (16%) relative to pure water at maximum salinity. A quadratic fit to the data was used in a ray optics model to explore the diffraction of ultrasound in fluid layers with varying sound speeds.   

Detection of Climate Change-Induced Underwater Sound Speed Variations in the Global Ocean Using Satellite Data and Machine Learning

Rising ocean temperature due to global warming caused several environmental alterations, such as rising sea levels, ocean acidification, and changes in underwater sound propagation. Investigation of sound speed variations due to global warming is necessary since sound propagation changes heavily impact underwater acoustic applications and threaten many marine lives. However, the global-scale study of sound speed variation is impossible in the traditional way, where sound speed is calculated from in-situ profiling measurements of temperature, salinity, and pressure, which is expensive and, therefore, limited in locations and time. Based on satellite observed sea surface data, we used a machine learning approach to predict sound speed for any given time and location in the global ocean. The results show that our model prediction had a root-mean-square error of 0.26 m/s and a coefficient of determination of 0.99. About 99% of the estimates lie within ±0.4 m/s of the sound speeds obtained from in situ temperature and salinity profiles. Since our model correctly identified the sound speed variations due to latitudes and seasons, it can be used to detect climate change-induced underwater sound speed variations in the global ocean.

    

Vibration of water surface excited by a vibrating object buried in sediment: simulation and measurements

The laser-acoustic detection of buried objects, such as landmines, uses elastic waves in the ground and a laser vibration sensor to create a vibration image of the ground surface. This method provides high probability of detection and low false alarm rate. Detection of landmines buried in underwater sediments is of great importance for humanitarian and military demining. However, extension of the laser-acoustic technique to underwater buried objects present a serious challenge due to the effects of the water layer. The presented work investigates the possibility of detection of an object buried underwater by sensing the vibration of the water surface. The vibration pattern of the water surface caused by an underwater buried vibrating object is simulated using COMSOL software. The simulation results are compared with laboratory measurements of the water surface vibration by using a scanning laser Doppler vibrometer. The results show how the vibration pattern of the water surface varies with the height of the water layer.   

Acoustic Array Processing in High Noise Environments

Microphone arrays have many practical applications in acoustics including both battlefield acoustics and sonic anemometry. These can be used to measure several types of acoustic signals: short-term transients, long-term transients, and coherent stationary signals. With a microphone array, signal processing techniques can be used to increase the signal to noise ratio in high noise environments, and they can also be used to determine the direction of arrival of detected coherent signals. These signal detection and direction of arrival algorithms have broad applications both in and outside of the field of acoustics. This particular talk aims to explore the basics of utilizing a sensor arrays and signal processing techniques in acoustics and the advantages that they provide in high noise environments.   

Artificial Intelligence Controlled Articulating 3D Acoustic Array

Acoustic sensors have many useful applications within the realm of battlefield acoustics. The focus of this project was to create an acoustic array which will be equipped with acoustic sensors, or microphones, in order to gather information about signals of interest. For our particular applications, the signals of interest may be things such as impulsive sounds (e.g. explosions), continuous sounds (e.g. equipment), long term transients (e.g. vehicle passing by), etc. The goal was that this array utilizing artificial intelligence will be able to pivot on its axis and select which sensors to use in order to improve its accuracy for a particular incoming signal of interest. The microphones are positioned along an oblique arm, such that each will individually detect the sound wave at its location as it propagates across the sensors. The precise spacing between each microphone allows the array to derive information on the direction from which the sound is arriving. The articulating nature of the array also allows it to track detected signals of interest which are in motion with maximum accuracy.   

Vibrational characterization of a helical antenna used in satellite communication

Helical coils serve many functions in mechanical systems and are often subjected to a variety of impulsive forces. In this talk we examine the dynamics of a helix modeled after an L-Band helical antenna used for satellite communications in low Earth orbit (LEO). Since the components of a deployed satellite are not accessible, it is critical to understand the dynamics of the antenna given its position outside of the main body. The intent of this work is to identify the frequencies, shapes and Q-values of the vibrational modes of the helix subject to impulsive stimuli and evaluate changes due to environmental exposures and structural modifications. We report on coil-by-coil measurements of the spectra using eight distinct stimulus response polarizations. Two specific studies are emphasized in this talk. To gauge the sensitivity of the element to thermal variations under (LEO) conditions, we report on the impact of thermal cycling on the vibrational spectra of the helix. We also report on changes in the dynamic response of the helix due to the addition of structural support elements.