Automatic qualification of hull performance

Determining the performance of a ship's hull based on its speed, load and trim.

Intelligence Artificielle : performance d'une coque de navire

Background

  • Maritime transport (which represents 90 % of the commercial goods transported worldwide and 1/8th of the energy consumed in the transport sector) is constantly growing.
  • The IMO (International Maritime Organization) is working to reduce CO2 emissions by 70 % by 2050.
  • Optimising ship hulls could reduce their consumption and thus their environmental footprint by 10 to 20 %.

Development of an automated process to generate and perform complex simulations and process data obtained from machine learning libraries.

OSE's missions : Modelisation & Simulation Computer Science

  • Generation algorithms, automatic mesh optimisation and parametrisation
  • Undertaking fluid mechanics calculations to estimate the forces applied to the hull of a ship, factoring in all possible operational profiles
  • Implementing design of experiments to optimise the number of simulations to be carried out
  • Using machine learning to generate the behavioural model of the ship as the simulations progress
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Intelligence artificielle : performance d'une coque de navire

Benefits of OSE's solution

  • A prediction model allows for multiple applications, from the choice of navigation parameters to defining the optimal hull shape.
  • Automation reduces research time and costs without compromising accuracy.

2 OSE developers mobilised

In 6 months

Patent filed and brought to market in partnership with MARORKA