A general cause based methodology for analysis of common cause and dependent failures in system risk and reliability assessments

Andrew O'Connor, Ali Mosleh
2016 Reliability Engineering & System Safety  
Traditional Probabilistic Risk Assessments (PRAs) model dependency through deterministic relationships in fault trees and event trees, or through empirical ratio common cause failure (CCF) models. However, popular CCF models do not recognized system specific defenses against dependencies and are restricted to identical components in redundant configuration. While this has allowed prediction of system reliability with little or no data, it is a limiting factor in many applications, such as
more » ... ng the characteristics of a system design or incorporating the characteristics of failure when assessing the failure's risk significance or degraded performance events (known as an event assessment). This paper proposes the General Dependency Model (GDM), which uses Bayesian Network to model the probabilistic dependencies between components. This is done through the introduction of three parameters for each failure cause which relate to physical attributes of the system being modelled, component fragility, cause condition probability, and coupling factor strength. Finally this paper demonstrates the development and use of the GDM for new system PSA applications and event assessments of existing system. Examples of the quantification of the GDM model in the presence of uncertain evidence are provided.
doi:10.1016/j.ress.2015.06.007 fatcat:mcmmseoiq5atta3yisyij3vioa