Journal
SHIPS AND OFFSHORE STRUCTURES
Volume 16, Issue 2, Pages 135-143Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/17445302.2019.1710936
Keywords
Wind farm support vessel (WFSV); docking; Monte Carlo; bivariate distribution; offshore wind turbine; wind energy
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This paper focuses on predicting extreme motions during WFSV operation and studying safety concerns when docking against wind towers, using AQWA software to analyze vessel response to hydrodynamic wave loads under actual sea conditions. A novel method for estimating bivariate statistics, based on Monte Carlo simulations, is outlined to mitigate excessive motions and reduce risks to crew during certain sea conditions.
Robust prediction of extreme motions during wind farm support vessel (WFSV) operation is an important safety concern. In particular, it is important to study safety of operation in random sea conditions during WFSV docking against the wind tower, while workers are able to get on to the tower. Docking is performed by thrusting the vessel fender against the wind tower (the alternative docking maneuver by hinging is not studied here). In this paper, the finite element software AQWA has been used to analyse the vessel response due to hydrodynamic wave loads, acting on a specific maintenance ship under actual sea conditions. Excessive motions may occur during certain sea conditions, posing a risk to the crew transfer operation. This paper presents a novel method for estimating bivariate statistics, based on Monte Carlo simulations (or measurements if available). The bivariate average conditional exceedance rate (ACER2D) method is briefly outlined.
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