ENGYS Participates in AI4TwinShip: Real-Time Design and Optimization of Marine Vehicle Hulls

ENGYS is proud to announce its participation in the AI4TwinShip project, a cutting-edge initiative aimed at revolutionizing the design and optimization of ship hulls using advanced artificial intelligence (AI) techniques coupled to Computational Fluid Dynamics (CFD) and mesh morphing. The primary objective of AI4TwinShip is to develop and demonstrate a new service for real-time prediction of ship hull resistance and other hydrodynamic performance metrics. This innovative approach leverages an AI-based model trained using a comprehensive database of CFD results to enhance the efficiency, performance and environmental sustainability of marine vessels.

The project relies on several key simulation technologies to achieve its ambitious goals. HELYX and HELYX-Marine, an open-source CFD software developed by ENGYS, will be employed to generate the database of CFD results; NAVPACK, provided by NAVASTO, will be used for training the AI models; and RBF Morph Stand-Alone, developed by RBF Morph, serves as a mesh morphing tool to parameterize ship hull shapes and automate the entire simulation process.

AI4TwinShip focuses on demonstrating the use of AI for real-time calculation of ship hull resistance. The AI models, trained with machine learning algorithms based on CFD results, are expected to provide accurate predictions of hydrodynamic characteristics to optimize ship hull shapes for reduced fuel consumption and minimal environmental impact. This project not only aims at improving the safety and operational efficiency of marine vessels, but also contributing to the creation of digital twins as an essential tool for modern naval design and optimization.

The project covers four main tasks: parametrizing hull shapes using mesh morphing to generate multiple ship hull configurations for the CFD, characterizing ship hull hydrodynamics using CFD techniques, training AI models and calculating the resistance of new hull designs in real-time using AI models. This methodology, already tested and validated by ENGYS for other industrial applications (e.g. automotive and motorsport), is anticipated to significantly reduce fuel consumption and greenhouse gas emissions, while enhancing the overall design and performance of marine vessels.

Project Duration: 12 Months

Budget: 213.635,80 €

Partner List: ENGYS


Click here to download the project poster.

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