Go-flow platform for time-dependent system reliability modeling and analysis

Reliability is an essential foundation for ensuring the safe operation of industrial systems. As the industrial automation has advanced significantly in recent years, the increase in system functionality and complexity has also posed a big challenge to reliability modeling and analysis of time-dependent behaviors and phased-mission problems involved in the system operations. In the paper, a GO-FLOW platform is developed with the integration of various functional modules including automated modeling, reliability quantification with minimum cut sets (MCSs) and minimum path sets (MPSs) generation, common cause analysis, path planning for mission survivability, and component-based paradigm for Living PSA applications. This GO-FLOW platform aims to provide an efficient solution for the time-dependent reliability modeling and analysis of industrial engineering systems. Among them, the automated modeling is implemented by converting the system flowchart directly into GO-FLOW model. The generation of minimal path sets and minimal cut sets are achieved through signal flow analysis and graph search algorithm. The quantification of time-dependent mission reliability is calculated alongside the qualitative analysis process based on the law of total probability. The common cause failure analysis covers the most commonly used parametric models, include Alpha factor model, Beta factor model, and the Multiple Greek Letter (MGL) model. Besides, a synthesis component-based paradigm is also proposed for Living probabilistic risk assessment and risk monitor applications in nuclear engineering. The GO-FLOW platform can not only guarantee the intuitiveness and consistency in system reliability modeling but also provide a tool for system design optimization and risk management, demonstrating broad application prospects.