A Markov resilience assessment framework for tension leg platform under mooring failure. (March 2023)

• Record Type: Journal Article
• Authors: Wu, Jingyi; Yu, Yang; Yu, Jianxing; Chang, Xueying; Xu, Lixin; Zhang, Wenhao
• Is Part Of: Reliability engineering & system safety. Volume 231(2023)
• Publication Date: 2023-03
• Subjects: Markov models -- Resilience -- Mooring failure -- Extreme ocean environment -- Recovery -- Single extreme event fatigue; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2022.108939
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: Novel resilience assessment framework for TLP under mooring failure is generated. The failure process and recovery process are modeled by Markov process and continuous-time Markov process, respectively. Two resilience metrics are defined to measure different aspects of resilience. The effect of extreme environment, structural degradation, recovery rate and strength on system resilience is considered. Abstract: During the service life of Tension Leg Platform (TLP), it may be exposed to various risk, with mooring failure being one of the most catastrophic events. Resilience, as an integrated assessment philosophy, can evaluate the overall post-event response performance and further improve system's operation safety. In this paper, a Markov resilience assessment framework for TLP under mooring failure is firstly proposed. The failure process and recovery process are mathematically described by Markov process and continuous-time Markov process, respectively. The internal and external effect has been taken into account, including extreme environment, structural degradation, recovery process schedule and structural strength etc. The resilience assessment framework is developed by 2 aspects, including robustness and recovery resilience. Besides, an illustrative example is developed as a walk-through of proposed methodology. The applications here demonstrate the versatility of the Markov framework towards handling resilience problems with varying levels of complexity, especially the offshore structure systems.