Metocean Advances
Monday, 5 May
600
Technical Session
The session presents the latest developments in forecasting techniques using machine learning, with application to the Gulf of Mexico Loop Current and eddies. In addition, it includes studies to characterize the Loop Current system in numerical models and solitary internal waves. The session demonstrates applications of metocean data and methods to oil spill detection, design of offshore renewable facilities and calibration of safety factors.
Session Chairpersons
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0200-0218 35839Calibration Of Weather Dependent Mooring Line Tension Safety Factors
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0220-0238 35559Methods In Metocean Data Processing And Loading Design Basis For Offshore Renewable Projects
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0240-0258 35531Metocean Data Analysis Methodology Based On Hindcast Data
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0300-0318 35614Response-based Forecasting Of Vessel Motion: From Physics-based To Data-driven Models
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0320-0338 35733A Spatiotemporal Machine Learning Framework For The Prediction Of Metocean Conditions In The Gulf Of Mexico: Application To Loop Current And Loop Current Eddy Forecasting
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0340-0358 35859Estimating Numerical Model Skill And Representativeness Of Kinematic Properties Of The Loop Current System In The Gulf Of Mexico.
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0400-0418 35812Solitary Internal Wave Characterization Southeast Of Trinidad And Tobago
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Alternate 35878Forecast Model Based On Hindcast Data Using Ai And Machine Learning
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Alternate 35760Optimizing Offshore Operations: Automated Oil Spill Detection Via Secure Data Sharing