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A Bayesian Network Model for the Probabilistic Safety Assessment of Offshore Wind Decommissioning

Shafiee, Mahmood, Adedipe, Tosin (2022) A Bayesian Network Model for the Probabilistic Safety Assessment of Offshore Wind Decommissioning. Wind Engineering, . pp. 1-22. ISSN 0309-524X. (In press) (doi:10.1177/0309524X221122569) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:96332)

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https://doi.org/10.1177/0309524X221122569

Abstract

With increasing the number of wind turbines approaching the end of their service life, it has become crucial for businesses to understand and assess safety and security issues related to the decommissioning phase of wind farm asset lifecycle. This paper aims to develop, for the first time, a Bayesian Network (BN) model for the safety assessment of offshore wind farm decommissioning operations. The most critical safety incidents are identified and their corresponding risk-influencing factors (RIF) are determined. The impacts of human errors as well as procedural and mechanical/electrical failures on the safety and efficiency of decommissioning operations are thoroughly analysed. The findings of the study revealed that the most critical RIFs during offshore wind decommissioning operations include: visibility, crew fatigue, number of personnel per operation, proper safety procedures, crane integrity, number of lifts available in the wind farm, inspection frequency, as well as equipment design.

Item Type: Article
DOI/Identification number: 10.1177/0309524X221122569
Uncontrolled keywords: Bayesian Network (BN); Offshore wind; Decommissioning; Safety assessment; Lifting operations; Risk-influencing factors; Influence diagrams
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA401 Materials engineering and construction
T Technology > TJ Mechanical engineering and machinery
V Naval Science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Mahmood Shafiee
Date Deposited: 22 Aug 2022 11:37 UTC
Last Modified: 03 Sep 2022 08:07 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/96332 (The current URI for this page, for reference purposes)
Shafiee, Mahmood: https://orcid.org/0000-0002-6122-5719
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