The world’s first AI-based ship design platform, NeuralShipper, developed by Compute Maritime, has announced the results of the UK government-funded GenDSOM project.
According to sea-news.az the project focused on designing a next-generation Crew Transfer Vessel (CTV) intended to service offshore wind farms.
Simulation results show that the vessel can save 101,671 liters of fuel per year and reduce CO₂ emissions by 258.7 tons compared to conventional equivalents.
The 32.5-meter catamaran-type vessel, designed to carry 24 technicians and 4 crew members, features a hull optimized using artificial intelligence and is equipped with a diesel-electric hybrid propulsion system. As a result, annual fuel consumption is reduced by 11.1%, while carbon emissions decrease by 8.9%.
The project also tested the use of 3D printing technologies for manufacturing ship components. The design additionally considers future integration with fast offshore charging systems, which could further improve efficiency.
Experts estimate that such an approach could reduce total emissions by up to 95% over a 25-year operational lifespan, marking a significant step toward more sustainable maritime transport.
