Trajectory prediction for drifting ship allision probability calculations

Trajectory prediction for drifting ship allision probability calculations: A trajectory prediction-based method for probability calculations to improve our understanding of drifting ship allision risks in the Dutch North Sea region

Eppenga, Sietse (TU Delft Mechanical Engineering)

van Koningsveld, M. (graduation committee)
van der Werff, S.E. (mentor)
van der Hout, A.J. (graduation committee)
van Gelder, P.H.A.J.M. (graduation committee)
Van Aartsen, Simon (graduation committee)

Delft University of Technology

Offshore and Dredging Engineering

2024-06-20

The expansion of offshore wind farms in the North Sea has raised serious concerns about maritime safety, in particular the increased risk of collisions—or 'allisions'—where a ship adrift hits a stationary structure, such as a wind turbine. For Rijkswaterstaat, the executive agency of the Ministry of Infrastructure and Water Management, managing this expansion requires developing a comprehensive understanding of the integral image of allision risks of drifting ships in the Dutch North Sea region. This understanding must be valid, reliable, and insightful, and include factors such as dynamic weather conditions and shipping activity. Unfortunately, current state-of-the-art methods for estimating the probability of allision rely heavily on assumptions, leading to significant variations in risk estimates, as highlighted by Ellis et al. (2008). These methods usually lack a North Sea-wide perspective and instead focus on risks specific to individual turbines.
This study proposes an approach based on trajectory prediction using the OpenDrift model, which is simple and accessible for simulating ship drift trajectories based on wind, wave, and current data. A method is developed to estimate the probability of allision by combining the probability of a ship drifting into a wind farm, analysed through a ship's potential trajectories, with ship density data for specific locations. This method facilitates the calculation of allision risks under the influence of different environmental conditions and can be applied to multiple wind farms, providing a detailed assessment of the origins of potential threats and available response times.
Overall, the assumptions in state-of-the-art methods might not sufficiently capture the risks associated with drifting ships. In addition, the established method broadens the ability to improve monitoring accuracy and optimise the positioning of ERTVs, even for specific environmental conditions. As a next step, this method should be extended to estimate actual risk levels by considering the potential consequences of an allision. With this approach, decision-making regarding allision threats can be contextualised alongside other maritime safety risks, facilitating the development of a robust risk mitigation strategy that enables Rijkswaterstaat to responsibly exploit the abundant potential the North Sea has to offer.

drifting
allision
ship
vessel
probability

http://resolver.tudelft.nl/uuid:cff6c8fc-9608-4e13-92c0-80a0201545bb

Student theses

master thesis

© 2024 Sietse Eppenga