Estimation of Mine Case Burial in a Mud-Covered Sea Bottom Using Acoustic Impedance Values Obtained from a Shipboard Fathometer
Abstract
A 12 kHz Bottom Sediment Classification "BSC" system that characterizes the seabottom according to acoustic impedance estimates was used to obtain normal incident acoustic data for determination of bottom sediment composition in Southeast Pass Louisiana near the mouth of the Mississippi River, and in an area offshore Corpus Christi Texas. The BSC uses the bottom and subbottom echo from a hull mounted transducer or transducer array to determine the acoustic impedance of the upper 50 cm of the sediment beneath the ship. A two-dimensional display of the sediment profile along track and a plot of the ship tracks, colorized to represent the composition of the seafloor, are provided in realtime to enable shipboard personnel to estimate bottom composition while the ship is underway. Acoustic data and screen images of the acoustic profiles are recorded to hard disk for additional review, data archiving, and post- mission laboratory analysis. A similar version of this system using Through-The-Sensor "TTS" technology has been successfully demonstrated aboard four US Navy mine countermeasures "MCM class" ships over the past three years. Predictions of bottom composition, i. e. sand or mud, provided on the BSC displays were used to select sites for an impact burial prediction study using cylindrical mine-like shapes. Approximately forty-eight separate cylinder deployments were conducted in muddy sea-bottoms at several different locations within two study areas in East Bay Louisiana and near Corpus Christi Texas. Subsequent to deployment, divers measured and recorded penetration depth of each shape in the seafloor. Sediment samples obtained by gravity and diver cores at each deployment site were used for ground truth assessment of sediment physical and geo-acoustic properties.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 2004
- Accession Number
- ADA480492
Entities
People
- Andrei Abelev
- Donald J. Walter
- L. D. Bibee
- Philip J. Valent
Organizations
- United States Naval Research Laboratory