Advancing Autonomous Underwater Vehicle Capability for Assessment of Marine Pollution
Application Id: | RGPIN-2021-02506 | ||
Competition Year: | 2021 | Fiscal Year: | 2021-2022 |
Project Lead Name: | Bose, Neil | Institution: | Memorial University of Newfoundland |
Department: | Ocean and Naval Architectural Engineering | Province: | Newfoundland and Labrador |
Award Amount: | $27,000 | Installment: | 1 - 5 |
Program: | Discovery Grants Program - Individual | Selection Committee: | Mechanical Engineering |
Research Subject: | Modelling, simulation and finite element methods | Area of Application: | Oceans, seas and estuaries |
Co-Researchers: | No Co-Researcher | Partners: | No Partners |
Marine pollution is a global environmental problem that has severe adverse environmental and socio-economic impacts. Oil spills are one form of pollution; further chemical run-off and plastics in the ocean are others. Climate change and severe degradation of our ecosystem are some of the outcomes from this pollution. Increased risks, the Deepwater Horizon blowout in the Gulf of Mexico, the MV Wakashio in Mauritius, spills off Newfoundland in 2018 and 2019, have broadened the gap between the potential need for oil spill countermeasures and current response capabilities. Information about oil and other pollution in the water column is critical to understanding of subsurface plume behavior which in turn enables timely and effective mitigation. Following the Gulf of Mexico blowout, the autonomous underwater vehicle (AUV) Sentry was successfully used to characterize submerged oil that was trapped at a depth of approximately 1200 m and provided a comprehensive analysis of the impacted areas. In this research AUV capabilities will be advanced specifically for the understanding of marine pollution and response: Firstly, an innovative adaptive mission planning approach for discontinuous patchy plumes made up of non-soluble oil droplet clouds or other potential items of interest such as micro-plastics, will be researched to improve performance of AUVs and their onboard sensors in delineating subsurface plumes. Using adaptive sampling, the AUV autonomously modifies its mission path in real-time based on features of the plumes detected by on-board sensors. Hence the AUV path is concentrated within the areas of interest and in information-rich areas identified by the sensors, optimizing the AUV response. Secondly, long-range AUV capability will be researched in conjunction with Canadian AUV manufacturers to enable extensive high-endurance marine pollution monitoring tasks to be completed with the aim to put in place watchdog and alerts that lead to mitigation measures. Renewable-energy battery charging at the water surface coupled with autonomous navigation and collision avoidance systems, similarly to those being developed for autonomous shipping, will be incorporated to enable these new designs of AUVs to operate safely over long periods in the ocean surface environment. Thirdly, risk-based analysis of these remote long range operations required for the monitoring of marine pollution will be researched and new methods will be developed to ensure that the risks of AUV deployment to other ocean users, such as people, ships and boats, as well as to the environment through underwater noise and the potential for pollution, are minimized. This is an essential component as an increasing number of autonomous vehicles populates the ocean surface. The target community of this research includes regulators, marine pollution agencies, oil spill response organizations, the offshore petroleum industry, AUV manufacturers, operators and oceanographers.
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