CFD Methodology for Slim
Vessel Regulation Testing
For the past two years, Damen has been working on a CFD-based research project called “Gone With The Wind” (GWTW) to study the capability of CFD to accurately model the aerodynamic forces that act upon vessels above the waterline. The specific issue being addressed has been the challenge of meeting the requirements of the IMO regulation 749.18. Its objective is to ensure that vessels have sufficient transversal stability to resist over-rolling in severe side winds. It is difficult for long, slender vessels to satisfy the empirical requirements of the rule without undertaking extensive and costly experimentation.
This has a direct impact on the time needed and the cost of gaining certification for vessels such as Damen’s monohull fast crew suppliers (FCS) and their variants. Typically, data have to be gathered from physical assessments using scale models in towing tanks and wind tunnels. The objective of GWTW has been to develop a CFD methodology to replace the physical assessments for vessels such as Damen’s FCS range that will demonstrate compliance to the satisfaction of the classification societies.
Damen has been developing the CFD methodology in partnership with Numeca while conducting the physical tests needed to validate and verify the CFD calculations, using a 1:18 scale model of Damen’s FCS 3307. Work is now underway to adapt this methodology to full-scale prediction.
SeaBat Sonar for Greenland
Seabed, Marine Mapping
The Greenland Climate Research Centre will take delivery of a Teledyne RESON SeaBat T50-R Extended Range high-resolution multibeam sonar early 2018. The sonar will be hull mounted on RV Sanna, a research vessel operating on the west Greenland coast. Researchers will utilize the sonar to map seabed topography and marine habitats in the 200- to 800-m deep waters of the Greenland Shelf.
Citizen Science Aids
Global Shark Research
Vital scientific information about whale shark behavior, biology and ecology is being uncovered by ecotourists and other citizens.
Whale shark habitat spans the globe, making long-term research over wide geographic ranges a challenge for whale shark researchers. Researchers have harnessed modern technology to create an online photo database called “Wildbook for Whale Sharks” and enlisted the help of ecotourists and citizens across the globe to upload any images of whale sharks they happened to see anywhere in the world. Photos of nearly 30,000 encounters representing 6,000 individually identified sharks across 54 countries over 22 years has given scientists a rich data set to analyze and better understand the nature of this endangered species.
Through this effort, researchers have now identified 20 whale shark aggregation sites globally.
ROV Video Informs
Deep-Sea Food Web Study
MBARI researchers have done the first comprehensive study of deep-sea food webs using hundreds of video observations of animals feeding off the central California coast. The study shows that deep-sea jellies are key predators and provides new information on life near the ocean surface.
Since the late 1980s, MBARI researchers have used ROVs to study deep-sea animals in their own environment. In the process, MBARI has amassed more than 23,000 hours of deep-sea video footage.
In this new approach, they used deep-diving vehicles to observe animals feeding on one another in the deep sea. Technicians in the MBARI Video Lab painstakingly analyzed every deep ROV dive, identifying animals and their behaviors and entering this information into the Video Annotation and Reference System (VARS) database. Combing through the VARS database, researchers discovered almost 750 different video observations of animals eating one another.
The video footage shows that jelly food webs encompass animals that live near the surface. Gelatinous animals have been found in the stomachs of animals ranging from penguins and albatrosses to sunfish and leatherback sea turtles.
AI for Eco-Friendly
Eco Marine Power (EMP) will begin using the Neural Network Console provided by Sony Network Communications Inc. as part of a strategy to incorporate artificial intelligence (AI) into various ongoing ship-related technology projects, including the further development of the Aquarius MRE renewable energy power system and EnergySail.
The Neural Network Console uses deep learning for AI creation and has been used in deep-learning applied technology development within Sony since 2015. Various functions include recognition technology and a full-fledged graphical user interface. Deep learning refers to a form of machine learning that uses neural networks modeled after the human brain.
An initial area of focus will be studying how the Neural Network Console and AI can assist with the development of the automated control system for EMP’s EnergySail. This system automatically adjusts the position of the EnergySail depending on variables such as wind speed and direction. AI will also help analyze the results of computer simulations related to the Aquarius Eco Ship.