engleski

The Assessment of Ship Damage Consequences by a Fast Simulation of Compartments Flooding

Recently, progressive flooding simulations have been applied onboard to support decisions during emergencies based on the outcomes of flooding sensors. To this end, both simulation accuracy and low computational effort are essential. A new mathematical formulation based on governing equations’ linearization can improve both these conflicting requirements, being more easily applied when calculation time is limited or a large number of flooding simulation has to be carried out. Besides, databases of flooding simulations together with machine learning algorithms can be exploited to assess the consequences of a damage scenario (final fate, flooded compartments time-to-flood) based only on the time evolution of the ship floating position (heel, trim and sinkage). The proposed method can be the base for a new generation of onboard decision support systems, which does not require the installation of flooding sensors, enabling cheap retrofit on most of the existing fleet.

damaged ship ; progressive flooding simulation ; emergency decision support ; machine learning

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