“…Many factors, such as daily usage of hazardous substances, equipment value, the degree of change in system performance, and the cost of recovery need to be considered to quantify the recovery ability. Due to the duration of an earthquake disaster being concise and aftershocks making the post-earthquake recovery mechanism very complicated, it is reasonable to simplify the recovery ability in the cross-regional level energy transmission system [51]. By assuming the damage of each pipe section in the OPNS subject to the Poisson distribution with the parameter Rr along the pipeline [52], the distance D i between two consecutive rupture points in each pipe section system in the OPNS exposed to earthquake can be calculated according to Equation ( 16), as follows:…”
Section: Quantification Of Recovery Abilitymentioning
The oil pipeline network system (OPNS) is an essential part of the critical infrastructure networks (CINs), and is vulnerable to earthquakes. Assessing and enhancing the resilience of the OPNS can improve its capability to cope with earthquakes or to recover the system’s performance quickly after the disturbance. This study defines the concept of OPNS resilience in the resistive ability, the adaptive ability, and the recovery ability. Then, the quantitative resilience assessment model is established considering the earthquake intensities, the role of safety barriers, the time-variant reliability, and the importance coefficient of each subsystem via a Monte Carlo simulation. Combining the model with GIS technology, a new methodology to evaluate OPNS resilience is proposed, and the resilience partition technology platform is developed, which can visualize the results of the resilience assessment. Finally, a case study is implemented to demonstrate the developed methodology, and a discussion is provided to identify the sensitive variables. The proposed resilience methodology can provide a framework for the probabilistic resilience assessment of OPNS, and could be expanded to other lifeline network systems.
“…Many factors, such as daily usage of hazardous substances, equipment value, the degree of change in system performance, and the cost of recovery need to be considered to quantify the recovery ability. Due to the duration of an earthquake disaster being concise and aftershocks making the post-earthquake recovery mechanism very complicated, it is reasonable to simplify the recovery ability in the cross-regional level energy transmission system [51]. By assuming the damage of each pipe section in the OPNS subject to the Poisson distribution with the parameter Rr along the pipeline [52], the distance D i between two consecutive rupture points in each pipe section system in the OPNS exposed to earthquake can be calculated according to Equation ( 16), as follows:…”
Section: Quantification Of Recovery Abilitymentioning
The oil pipeline network system (OPNS) is an essential part of the critical infrastructure networks (CINs), and is vulnerable to earthquakes. Assessing and enhancing the resilience of the OPNS can improve its capability to cope with earthquakes or to recover the system’s performance quickly after the disturbance. This study defines the concept of OPNS resilience in the resistive ability, the adaptive ability, and the recovery ability. Then, the quantitative resilience assessment model is established considering the earthquake intensities, the role of safety barriers, the time-variant reliability, and the importance coefficient of each subsystem via a Monte Carlo simulation. Combining the model with GIS technology, a new methodology to evaluate OPNS resilience is proposed, and the resilience partition technology platform is developed, which can visualize the results of the resilience assessment. Finally, a case study is implemented to demonstrate the developed methodology, and a discussion is provided to identify the sensitive variables. The proposed resilience methodology can provide a framework for the probabilistic resilience assessment of OPNS, and could be expanded to other lifeline network systems.
“…However, there is a noticeable scarcity of resilience assessment studies within offshore engineering. For instance, Ramadhani et al 6 conducted a study on the resilience of a monopile vertical structure under ice loads. They measured resilience using parameters such as absorption capacity, adaptive capacity, and recovery capacity.…”
Offshore floating structures rely heavily on their mooring systems, which can be disrupted by various events during long‐term operation. These could lead to a mooring failure, affecting the usual operations of the structure or even causing more severe hazards. Resilience provides a comprehensive evaluation of how the mooring system performs after a disaster, which is key to optimizing the structural design and operational safety. In this paper, we develop a general and user‐friendly method to quantitatively assess the resilience of mooring systems under mooring failure. We use the reliability index to represent the performance of the mooring system. We then derive its RV, ACI, and RCI, which are based on a system performance curve and reliability analysis. We also consider the effects of climate change and the corrosion of the mooring chain. These factors can significantly affect environmental loads, structural performance, and the recovery process. Moreover, an illustrative example is provided that guides us through the methodology. The proposed method is applied to assess the resilience of a certain mooring system in the South China Sea over a 30‐year service life under different failure scenarios. Our results indicate that overlooking climate change in the design and operation of the mooring system can lead to a significant overestimation of its reliability index and resilience value.
“…For instance, Wilkie and Galasso [18] proposed a methodology to evaluate offshore wind farm resilience by quantifying financial losses associated with offshore wind turbines. Ramadhani et al [19] investigated offshore structure response to an ice load using a resilience assessment approach. Hu et al [20] proposed marine liquefied natural gas (LNG) offloading systems' dynamic resilience model considering weather-related hazards.…”
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