Explicit and implicit Valuation-Based System methods for the risk assessment of systems subject to common-cause failures under uncertainty

Abstract

Multiple components within a system may fail or malfunction simultaneously due to a shared cause or common cause (CC). This kind of failure is referred to as a common-cause failure (CCF), and it contributes greatly to the system failure. Due to the insufficiency of relative data and system complexities, different kinds of uncertainties inevitably exist in real-world system modeling. This paper proposes explicit and implicit Valuation-Based System (VBS) methods to model systems subject to CCFs, and to evaluate the failure probability of such systems considering the parametric uncertainty related to state probabilities of components and the model uncertainty related to the system structure. Both methods are suitable to model systems subject to CCFs under different kinds of uncertainties, and allow the relationship among multiple CCs being s-independent, s-dependent or mutually exclusive. Finally, the proposed methods are applied to model hazardous material transportation accidents and to evaluate the occurrence probability of accidents using statistical data.