Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering Conference
Shanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

Probability Analysis Method of Collision Risk Between Ships in Channeland Offshore Wind Turbine Foundations
Xiaofang Luo1, Mengxia Xing1, Xu Bai2, Rongkeng Tang2
1. School of Economics & Management, Jiangsu University of Science and Technology
Jiangsu Zhenjiang, China
2. School of Naval Architecture & Ocean Engineering, Jiangsu University of Science and TechnologyZhenjiang, China

ABSTRACT1994). This makes the ship collision risk analysis of OWTF increasinglyimportant.
Geometric collision probability estimation is commonly used tocalculate the collision probability of ships, and some scholars strengthen
its accuracy by considering other factors. A simplified equation wasderived by Macduff (1974) to determine the geometric collision
probability based on the ship’s maneuverability and passage width. Fujiand Tanaka (1971) devised an equation that takes into account traffic
density and the relative speeds of colliding ships. Montewka et al.
(2012) investigated a new definition of ship collision criteria-theminimum collision distance. However, none of the above methods canquantitatively analyze the impact of different risk factors on collisionrisk events. Fault tree analysis (FTA) and Bayesian network (BN) arecommon methods to analysis risk. (Weber et al., 2012). FTA is usually
only used for two-state risk analysis, which is not as accurate as
analyzing accident probability directly through risk data information(Ma, 2015). BN can perform bidirectional reasoning analysis to assess
the importance of various risk factors in risk events, which is very
suitable for polymorphic system reliability analysis. Hence a fault tree(FT) was established to analyze the occurrence mechanism of risk
events qualitatively, and then converted it into BN to quantitatively
calculate the risk failure rate when studying the risk of position loss (Baiet al., 2020). The calculation of complicated causality probability
heavily relies on historical data quantified with an expert scoring
method. Data collected by expert scoring as input can improve theaccuracy of causal probability calculations (Dong, Frangopol, 2015).
Expert evaluation language is fuzzy and it is difficult to obtain accurate
probability. Therefore, TFN is proposed to reflect the predictedvariables judged by experts and calculate the exact probability of theroot node. However, Ma (2012) and Wang (2021) do not consider theambiguity of the logical relationship between different nodes. Without
sufficient incident records in the collision risk between ships andOWTFs, some data collection methods were proposed by scholars
extrapolating data and information from similar operations in theoffshore oil and gas industry was emphasized by Dai (2013). But thedifference of collision subjects and factors results in the lack ofAt present, a number of offshore wind farms have been built in China
and some of these offshore wind farms (not minority) are located on thesides of shipping lanes. This will lead to a certain risk of collision
between the sailing ship and offshore wind turbine foundations due tothe sailing direction deviation. So, the research on the risk assessment ofoffshore wind turbine collision with sailing ship cannot be ignored. This
paper studies the occurrence probability of these collision risks. Multistate Bayesian network is established by investigating the risk factors ofcollision between offshore wind turbine foundation and sailing ship.
When calculating the probability of collision risk, the analytic hierarchy
process and triangular fuzzy number are combined with expert scoresand historical data to calculate the conditional probability table. The
calculation result of the drift/dynamic collision probability are 0.04599
and 0.03879. Then, the mooring system fault f06 and steering gear fault
f06 are the key factors leading to the risk of drift collision and dynamic
collision, and should be timely checked during the ship navigation. This
probabilistic analysis method can be used in the study of various risk
events and the paper result holds a significant meaning to promote thesafety management level of collision between offshore wind turbine
foundation and sailing ship.

KEY WORDS:ship; offshore wind turbine foundation; risk
probability; collision; multi-state Bayesian network.

INTRODUCTION
With the rapid construction and development of offshore wind farms,the collision between ships and offshore wind turbine foundation(OWTF) is one of the main risks in the operation of offshore wind farms(Zhang, 2014; Moulas, 2017). At present, the construction of offshore
wind farms is generally close to the waterway, which affects the passageof ships. In addition, due to the large tonnage of transport vessels,serious collision accidents (environmental pollution, economic loss,casualties) will be caused once collisions occur (Shi et al., 2018; Bea,389