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Remote Sensing

Distributed Chemical Sensing for Sub-surface Oil Spill Sensing

Principal Investigator has worked on: (1) Polycyclic Aromatic Hydrocarbon (PAH) sensing by Surface-Enhanced Raman Scattering (SERS) and (2) Hydrocarbon and crude sensing by Localized Surface Plasmon Resonance (LSPR) and Surface-Enhanced Near-Infrared Absorption (SENIRA). The final test was conducted at Ohmsett in November 2016, and the research team demonstrated the detection and quantification of various polycyclic hydrocarbon species.

OSRR-1039-Oil Leak Detections with a Combined Fluorescence Polarization Instrument and a Wide Band MultiBeam Sonar

This project’s objective was to develop and test a prototype sensor that integrates two partial solutions (fluorescence and sonar) with a goal of operating at a suitable standoff distance and interrogating a wide area, while providing real-time data feed from the subsea environment. The project was conducted in two phases. 

Phase 1 objectives:

OSRR-1037-Development of an Autonomous Oil Skimmer (AOS)

The goal of this project was to develop a strap-on navigation, sensor, and computer control system that could be used to direct a variety of commercial off the shelf (COTS) skimmers and vessels to autonomously maneuver and skim the oil from a given area with automatic tracking and reporting of progress and performance. This autonomous oil skimmer (AOS) system consisted of a commercial of the shelf (COTS) skimmer and vessel, a COTS autopilot system, a high precision navigation package, oil thickness and recovery efficiency sensors, and a custom computer algorithm.

OSRR-1031-Innovative Technology Enhancements for Measuring Test Parameters at Ohmsett

The objective of this project is to provide Ohmsett with the capability of remotely calculating oil and ice coverage, as well as determining thickness. Accurate, rapid, and facilitated assessment of cold water and ice testing parameters such as total surface oil versus ice area coverage and oil layer thickness in the Ohmsett facility test tank can best be accomplished using imaging technologies.

OSRR-1028-Acoustic Tool to Measure Oil Slick Thickness at Ohmsett

The objective of this project is to develop an acoustic tool to measure oil slick thickness at Ohmsett from a Remotely Operated Vehicle (ROV). The ROV will be designed as a simple, low cost acoustic-based ROV with the ability to resolve oil slick thickness from ~500 microns to over three centimeters. It will be outfitted with acoustic sensors, video sensors and sonar which will be mounted above two tracks that will be used to drive the sensors along the bottom of the Ohmsett wave tank.

OSRR-1021-Evaluation of Oil in the Water Column Detection Systems

This project's objective was to track the movement of subsurface oil in the nearshore areas. Efforts were directed towards evaluating two portable prototype systems designed to detect oil in the water column. These prototype systems include:

Wide Band Multibeam Sonar by Norbit Optical Tool using Wide-Angle-Scattering Inversion with Fluorometer backup by WET Labs

These systems were evaluated at the National Oil Spill Response and Renewable Energy Test Facility (Ohmsett) in November, 2013.

OSRR-1008-CORN (Coordinated Oil-spill Response Network)

The objective of this project is to develop a Coordinated Oil-spill Response Network (CORN) which will benefit response command centers by enabling them to provide clear mission profiles to vessels, share up-to-date oil spill/response information, collect field data for input into models used to reflect and predict conditions, and maintain and distribute a Common Operational Picture across all participants.

OSRR-1000-Oil Spill Detection and Mapping Under Arctic Sea Ice using Autonomous Underwater Vehicles

Objective/Goal: The goal of this project was to evaluate and develop an AUV-based system for detection and mapping of oil in ice-infested waters from below the water and/or ice. The two main elements of this effort were: Extensive laboratory ice-tank tests to test and evaluate each candidate sensor, and provide a 'fit-for-purpose' AUV-based sensor suite to detect and quantify the thickness of oil under sea ice from below the ice.

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