ABSTRACT

In recent years, the interest in the applicability of Bayesian Networks (BN) to the Reliability and Risk Analysis of complex systems has increased. BNs are powerful probabilistic models to build the causal relationships between events and applicable failure modes of a system. One important feature of BN is the possibility of including evidences about the system state on the system model to reassess the probabilities of network events. Given some evidence, beliefs are recalculated to indicate its impact on the network. This feature may be used to provide several analyses of different scenarios to obtain information such as the critical components, the influence of environmental conditions on the system, the impact of including redundancies, the impact of common cause failures and any other condition that affects the system reliability. This paper presents an application of BN to analyze different event scenarios by computing the posterior marginal probability distribution of each component, the computation of the posterior joint probability distribution on subsets of components, and the computation of the posterior joint probability distribution function of the set of all nodes. As an application, this study will perform the analysis of the behavior of a Liquefied Natural Gas (LNG) Regasification System on a Floating Storage and Regasification Unit (FSRU). Currently, Liquefied Natural Gas Import Terminals (where the storage and regasification process is conducted) are mostly onshore; the construction of these terminals is costly, and many adaptations are necessary to abide by environmental and safety laws. The FSRU can be viewed as an option for LNG storage and regasification. The results clarify how the use of BNs to analyze different scenarios may provide relevant data about the system behavior and improve reliability and risk analysis.

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