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Enhancing the ability to predict ship and system response in rough sea conditions, reducing risk, and optimizing navigation decisions using cutting-edge maritime environmental data, AI, and optimization algorithms.
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PrISM_MSEM System On-board reassessment of seaconditions for marine operations by Christophe Capitant (presented by Christophe Maisondieu)
PrISM_MSEM System • The context : • SAR operations at sea • Most of the time in rough sea conditions • Require ability to predict the response of ships and other systems with accuracy and in a reliable way • « Trial and error » : not an option • Quick investigation of many alternatives
PrISM_MSEM System • The current maritime situation : • Factors that produce maritime incidents : • Diversity of older vessels and state-of-the-art ships • Reduced crew • Areas of high density shipping • Increasing levels of traffic and higher transit speeds • Commercial requirements force ‘ short-cuts ’
PrISM_MSEM System • Increased risk in marine operations due to : • Severely limited ‘ sea sense ’ when in rough sea conditions and/or hazardous situations such as towing, rescue operations, damage control, etc…. • Managementof multiple and concurrentnavigation issues : (security, ship motion, structural stress, transit speed optimisation, etc…) • Difficulty to provide all the relevant information to the final human decidersin a useful form.
PrISM_MSEM System • The current requirements : • Choice of the best course under meteorological and operational constraints : • Assess the consequences of the various options in extreme situations before taking the decision • Shorten the decision process • Increase navigation accuracy • Limit ship fatigue and risk of failure • Avoid serious damage and possiblepollution
PrISM_MSEM System • Our option : • Enhance local sea-state forecast. • Use EO enhanced forecast • to predict the ship or system response • to further enhancethe local forecast by comparing with observed ship response. • to simulate the ship behaviour even after a change in the course.
PrISM_MSEM System • The mean : PrISM • a system developed for helicopter deck-landing operations • and adapted to other marine operations. • Main features : • Implementation of cutting-edge maritime environmental data and ship motion models • Use of Artificial Intelligence : • System adapts automatically to the real time measured sea-state using genetic algorithms • Emulation of the human decision-making process by use of fuzzy logic • Implementation of highly efficient optimisation algorithms (multi-parameters: roll, bending moment, towline tension, ...)
PrISM_MSEM System • PrISM main results : Operational simulations show : • Significant reduction of the inaccuracies in the local sea-state models • Reduction of the global ‘energy density spectrum’ of the response of the ship when selecting the solution recommended by the system, i.e. : • reduced ship motion • reduced structural stress • Optimisation of the navigation course in terms of safety
PrISM_MSEM System The Ship and Marine Environment Model Interface
PrISM_MSEM System The Self-Adaptation of the Sea-State Interface
PrISM_MSEM System The Motion and Structure Management Interface
PrISM_MSEM System The Route Optimisation Management Interface
PrISM_MSEM System The Navigation Management Interface
Forecast Forecast +EO PrISM_MSEM Best Local Sea-State PrISM_MSEM System • Projects : • CAMMEO • Co-Ordinated Approach to Markets for Marine Earth Observations • Would assimilation of Earth Observations measurements in forecast enhance the ability of the PrISM_MSEM system to accurately evaluate the local Sea-state ?
PrISM_MSEM System • Projects : • CAMMEO • Assessment and validation tests • on-board R/V THALASSA • November 2004 • Bay of Biscaye
PrISM_MSEM PrISM_MSEM System • Proposal : • SARASSEN • SAR ASSistant for Enhancement of Navigation • Develop, install and test a full system on-board SAR vessels : HYDRODYNAMICS SOLVER (Tow-line and assisted ship dynamics) FORECAST Sea-State Input Data Local Sea-State Best course/speed options