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I3-Project: Predicting Ship Hydrodynamics to Enable Autonomous Shipping: Nonlinear Physics and Machine Learning

This I3-project addresses hydrodynamics of autonomous ships in waves as one of the key steps along the development path leading to fully autonomous ships. The main challenge is to create a cyber-physical system, controlled by computer algorithms and sensor-based environmental monitoring, to ensure collision avoidance, ship safety and economic efficiency as well as to reduce the environmental impact under arbitrary conditions in real time.

The objective of this I3-project is to create a general simulator-based test environment addressing the relevant environmental conditions, its hydrodynamics and structural consequences, thus creating a so called Digital Twin (DT) concept for ships and structures in waves. A further and more general objective is to develop a methodology for the exploration of ML as basis for decision making of autonomous ships and structures. Hereby, this I3-project will serve as initial and indispensable first step forming the basis for a long-time research focus. For this purpose, two DT are to be developed: one is based on physical and numerical models, and the other on machine learning (ML) algorithms.

Project Coordinator: Marco Klein

Funding: TUHH

Duration: 2 years