@article {6649, title = {Estimation of Environmental Parameters with Machine Learning Using a Compact Tetrahedral Array and Sources of Opportunity}, volume = {145(3)}, year = {2019}, month = {April 23}, pages = {1671-1671}, publisher = {Acoustical Society of America}, abstract = {

In a previous paper, we showed that we could localize sound sources using a compact tetrahedral hydrophone array in a continental shelf environment south of Block Island, Rhode Island. The tetrahedral array of phones, 0.5 m on a side, was deployed to monitor the construction and operation of the first offshore wind farm in the United States. Directions of arrival (DOAs) for a number of ships were computed using a time difference of arrival technique. Given the DOAs, ranges are estimated using supervised machine learning techniques. Here, we extend this work to estimate a number of environmental parameters including water depth and sediment composition. Training sets of range-dependent ocean waveguides and sediment sound speeds were generated using a propagation model for a neural network. Data from the tetrahedral array were processed by the neural network, which provided estimates of the water depth and sediment parameters such as sound speed and density. These estimates are compared to bathymetric data and core data collected as part of the site characterization for the wind farm. [Work supported by the Office of Naval Research and the Bureau of Ocean Energy Management.]

}, doi = {https://doi.org/10.1121/1.5101133}, author = {Moore, Jesse T. and Miller, J H and Potty, Gopu R. and Aditi Tripathy and Tazawa, M. and Jennifer Amaral and Newhall, Arthur E. and Ying-Tsong Lin} } @article {6650, title = {Characteristics of the soundscape before and after the construction of the Block Island Wind Farm}, volume = {144(3)}, year = {2018}, month = {October 18}, pages = {1856{\textendash}1856}, publisher = {Acoustical Society of America}, abstract = {

The Block Island Wind Farm (BIWF) south of Rhode Island is the first offshore windfarm in the United States. As part of the Ocean Special Area Management Plan, acoustic data were collected before the construction in the fall of 2009. Noise budgets were estimated based on this data and showed the dominant sources of sound in a 1/3-octave band centered at 500 Hz were shipping and wind. Data were again collected during and after construction of the wind farm and will be presented and compared to pre-construction levels. In 2009, Passive Aquatic Listener (PALs) were deployed. After construction was complete, data from a tetrahedral hydrophone array (~50 m from one of the wind turbines) were analyzed to study the soundscape from December 20, 2016 to January 14, 2017. The acoustic environment near the BIWF after construction showed contributions from shipping, wind, and marine life. Noise from the wind turbine was measured near 70 Hz at approximately 100 dB re 1 mPa at a range of 50 m. Significant marine mammal vocalizations were recorded including from humpback and fin whales. (Work supported by the Bureau of Ocean Energy Management.)

}, doi = {https://doi.org/10.1121/1.5068166}, author = {Aditi Tripathy and Miller, J H and Potty, Gopu R. and Jennifer Amaral and Vigness-Raposa, Kathleen J. and Frankel, Adam S. and Ying-Tsong Lin} } @article {6651, title = {Source Localization Using a Compact Tetrahedral Array}, volume = {144(3)}, year = {2018}, month = {October 18}, pages = {1745{\textendash}1745}, publisher = {Acoustical Society of America}, abstract = {

We localized sound sources collected on a compact tetrahedral hydrophone array in a continental shelf environment south of Block Island, Rhode Island. The tetrahedral array of phones, 0.5 m on a side, was deployed to monitor the underwater sound of construction and operation of the first offshore wind farm in the United States. Signals from shipping and marine mammals, including fin whales, humpback whales, and right whales, were detected on the array. Directions of arrival (DOAs) for a number of signals were computed using a time difference of arrival technique. Given the DOAs, ranges were estimated using supervised machine learning techniques outlined by Niu et al. (JASA, 2017). The approach was tested using simulated data from Kraken assuming environmental information consistent with this continental shelf environment. Performance on signals from individual ships and marine mammals is presented. Ship localizations are compared to Automated Identification System (AIS) fixes. An error analysis is also presented. [Work supported by the Office of Naval Research and the Bureau of Ocean Energy Management.]

}, doi = {https://doi.org/10.1121/1.5067739}, author = {Miller, J H and Potty, Gopu R. and Aditi Tripathy and Tazawa, M. and Jennifer Amaral and Vigness-Raposa, Kathleen J. and Ying-Tsong Lin} } @article {5180, title = {Experimental and Numerical Studies of Sound Propagation over a Submarine Canyon Northeast of Taiwan}, volume = {40(1)}, year = {2015}, month = {19 February 2014}, pages = {237-249}, publisher = {IEEE}, abstract = {

A study of sound propagation over a submarine canyon northeast of Taiwan was made using mobile acoustic sources during a joint ocean acoutic and physical oceanographic experiment in 2009.\ The acoustic signal levels (equivalently, transmission losses) are reported here, and numerical models of three-dimensional sound propagation are employed to explain the underlying phsyics.\ The data show a significant decrease in sound intensity as the source crossed over the canyon, and the numerical model provides a physical insight into this effect.\ In addition, the model suggests that reflection from the canyon seabed causes three-dimensional sound focusing when the direction of propagation is along the canyon axis.\ Environmental uncertainties of water sound speed, bottom geoacoustic properties and bathymetry are addressed, and the implications for sound propagation prediction in a complex submarine canyon environment are also discussed.

}, keywords = {3D Sound Propagation, North Mien-Hua Canyon, submarine canyons}, author = {Ying-Tsong Lin and Duda, Timothy F. and Emerson, Chris and Gawarkiewicz, Glen G. and Newhall, Arthur E. and Brian R Calder and Lynch, James F. and Abbot, Philip and Yang, Yiing-Jang and Jan, Sen} }