Probabilistic Estimation of Primary Ship-Induced Wave Heights at Estuary Groins Using a Nonparametric Bayesian Network

Rock groins in the Elbe Estuary are constructed to maintain proper water levels for navigation and for embankment erosion protection. At certain localities, significant damages to rock groins have been observed due to the primary ship-generated waves. Primary waves are generated along the ship’s hull and then propagate toward the river banks and groin fields, appearing in the interaction with the structures as a turbulent overflow phenomenon. Eventually, this overflowing may cause damages mainly to the crest and leeward side of the groins. Since this overflowing is the most pronounced with large primary waves at certain water levels, the estimation of the probabilities of extreme primary waves is a key element for a safe and reliable design of groins. For this goal, nonparametric Bayesian networks (NPBNs) are used here to infer the probability distribution function of the extreme primary wave heights at the tip of a groin in the Elbe Estuary. Results demonstrate the suitability of the NPBN in their prediction. The model framework allows the designer to predict the probabilities of primary ship-generated waves at groins when the information of ship dimensions, nautical parameters, and waterway geometry is available. These probabilities can later be used for design purposes for current and future conditions.

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Publication Details

Journal
Journal of Waterway Port Coastal and Ocean Engineering
Published
2025-04-07
DOI
https://doi.org/10.1061/jwped5.wweng-2063
Primary Topic
Maritime Navigation and Safety
Type
article
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article

Probabilistic Estimation of Primary Ship-Induced Wave Heights at Estuary Groins Using a Nonparametric Bayesian Network

Gregor Melling, Elisa Ragno, Sebastiaan N. Jonkman, Sargol Memar et al.
Journal of Waterway Port Coastal and Ocean Engineering
Maritime Navigation and Safety
article

Probabilistic Estimation of Primary Ship-Induced Wave Heights at Estuary Groins Using a Nonparametric Bayesian Network

Gregor Melling, Elisa Ragno, Sebastiaan N. Jonkman, Sargol Memar, Bas Hofland, Oswaldo Morales‐Nápoles, Patricia Mares Nasarre
article en

Abstract

Rock groins in the Elbe Estuary are constructed to maintain proper water levels for navigation and for embankment erosion protection. At certain localities, significant damages to rock groins have been observed due to the primary ship-generated waves. Primary waves are generated along the ship’s hull and then propagate toward the river banks and groin fields, appearing in the interaction with the structures as a turbulent overflow phenomenon. Eventually, this overflowing may cause damages mainly to the crest and leeward side of the groins. Since this overflowing is the most pronounced with large primary waves at certain water levels, the estimation of the probabilities of extreme primary waves is a key element for a safe and reliable design of groins. For this goal, nonparametric Bayesian networks (NPBNs) are used here to infer the probability distribution function of the extreme primary wave heights at the tip of a groin in the Elbe Estuary. Results demonstrate the suitability of the NPBN in their prediction. The model framework allows the designer to predict the probabilities of primary ship-generated waves at groins when the information of ship dimensions, nautical parameters, and waterway geometry is available. These probabilities can later be used for design purposes for current and future conditions.

Journal of Waterway Port Coastal and Ocean EngineeringVol. 151(4)
Bundesanstalt für Wasserbau (DE), Delft University of Technology (NL)
Life below water
Openalex Percentile: Top 91%
Maritime Navigation and Safety
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Probabilistic Estimation of Primary Ship-Induced Wave Heights at Estuary Groins Using a Nonparametric Bayesian Network — Gregor Melling, Elisa Ragno, et al. · Journal of Waterway Port Coastal and Ocean Engineering (2025) | TGRS Research Map | TGRS