Reliability assessment of flexible dolphins
Reducing uncertainty in the design approach of flexible dolphins
R.N. Bechan (TU Delft - Civil Engineering & Geosciences)
MZ Voorendt – Mentor (TU Delft - Hydraulic Structures and Flood Risk)
O.M. Heeres – Mentor (ARCADIS Nederland)
Pieter van Gelder – Graduation committee member (TU Delft - Safety and Security Science)
Alfred Roubos – Graduation committee member (TU Delft - Hydraulic Structures and Flood Risk)
JG de Gijt – Mentor (TU Delft - Hydraulic Structures and Flood Risk)
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Abstract
The abstract outlines a study focusing on improving the design approach for flexible dolphins, vital marine structures used for vessel berthing and mooring. Current design methodologies, particularly those outlined in the CROW C1005 handbook (2018), are questioned due to potential conservatism stemming from insufficiently calibrated partial factors. The study advocates for reliability-based assessments to address these concerns, which consider uncertainties inherent in dolphin design and quantify failure probabilities over their lifespan. The investigation identifies critical failure modes and determines main pile dimensions based on these modes, utilizing the API PY-curves for rapid computation in the design process. Probabilistic assessments, employing Directional Sampling, reveal the significance of berthing load in structural safety and identify soil parameters as dominant variables affecting fixity failure mode. Navigation conditions, ship arrival rates, and variation in ship sizes also influence partial factors, with recommendations provided for adjustments based on different conditions. The study suggests load testing to reduce uncertainties and increase reliability, exemplified by a Bayesian update from Calandkanaal full-scale load tests. Overall, reliability-based assessments yield insights into managing uncertainties in dolphin design, potentially reducing material usage by up to 20% while meeting safety requirements, and offering the potential to decrease failure probabilities tenfold when combined with test loading.