Resilience assessment of a subsea pipeline using dynamic Bayesian network

Journal of Pipeline Science and Engineering

Noor Quddus¹  Faisal Khan²  Rouzbeh Abbassi³  Mohammad Yazdi³ 

[1] Mary Kay O'Connor Process Safety Center, Artie McFerrin Department of Chemical Engineering Texas A&M University, College Station, TX, USA;School of Engineering, Macquarie University, NSW 2113, Australia;Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's NL A1B 3X5, Canada;

关键词: Pipeline;    Offshore;    Bayesian network;    Engineering resilience;    MIC;    Subsea system;   

DOI  :  

来源: DOAJ

【 摘 要 】

Microbiologically influenced corrosion (MIC) is a serious concern and plays a significant role in the marine and subsea industry’s infrastructure failure. A probabilistic methodology is introduced in the present study to assess the subsea system’s resilience under MIC. Conventionally, the risk-based models are constructed using the system’s characteristic features. This helps decision-makers understand how a system operates and how the failed system can be recovered. The subsea system needs to be designed with sufficient resilience to maintain the performance under the time-varying interdependent stochastic conditions. This paper presents the dynamic Bayesian network-based approach to model the subsea system’s resilience as a function of time. An industry-based application study of the subsea pipeline is studied to demonstrate the efficiency and effectiveness of the proposed methodology for the resilience assessment. The proposed methodology will assist decision-makers in considering the resilience in the system design and operation.

【 授权许可】

Unknown