| 🚢 TwinShip Interview: Where Physics Meets AI for Smarter and Greener Shipping How can the maritime sector combine traditional naval architecture, Digital Twins, Artificial Intelligence and real vessel data to make better decisions for future ships? In a recent TwinShip interview, Professor Kostas Belibassakis from the National Technical University of Athens (NTUA) shared his insights on how physics-based engineering and AI can work together to support safer, more efficient, and lower-emission shipping. 🌊 Hydrodynamics remains the foundation Understanding how a vessel interacts with water, waves and propulsion systems is essential for predicting resistance, power demand, manoeuvrability and overall performance. 📊 The big change: huge amounts of vessel data Modern sensors, telemetry and data-processing systems are transforming naval architecture. Operational data can now be combined with physical models to improve predictive capability and support smarter decisions. 🧠 AI should not replace physics — it should work with it Purely data-driven models may struggle when ships encounter unexpected or poorly represented conditions. TwinShip therefore explores physics-based and physics-informed Digital Twins, where engineering knowledge constrains and strengthens AI predictions. 🔹 Digital Twins as the foundation of Decision Support Digital Twins can support both short-term voyage decisions and longer-term strategic decisions involving vessel performance, future technologies, retrofits and lifecycle operation. ⚙️ Testing technologies on real vessels Within TwinShip, NTUA has developed prototype Digital Twins combining vessel design and operational data to assess alternative fuels, propulsion options, and emission-reduction potential. |
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| 🌱 There is no single solution for decarbonisation Their effectiveness depends on the vessel, route, and operating conditions, so the best technology can vary significantly between ships. 🎓 The naval architect of the future will need new skills Future maritime engineers will increasingly need knowledge of statistics, probability, data assimilation, algorithms and programming, while still maintaining a strong foundation in hydrodynamics, propulsion, CFD and ship design. 🤝 The real opportunity lies in closing the gap between engineering and data science. 🚢 TwinShip is helping build that bridge — combining physics, real-world vessel data and AI to give shipowners stronger evidence for selecting future fuels, technologies and operational strategies. 🌍 Physics tells us how ships should behave. Data tells us how they actually behave. AI can help connect the two. |