Time Dependent System Reliability Analysis Using Random Field Discretization

Abstract

This paper proposes a novel and efficient methodology for timedependent system reliability analysis of systems with multiple limitstate functions of random variables, stochastic processes, and time. Since there are correlations and variations between components and over time, the overall system is formulated as a random field with two dimensions: component index and time. To overcome the difficulties in modeling the twodimensional random field, an equivalent Gaussian random field is constructed based on the probability equivalency between the two random fields. The firstorder reliability method (FORM) is employed to obtain important features of the equivalent random field. By generating samples from the equivalent random field, the timedependent system reliability is estimated from Boolean functions defined according to the system topology. Using one system reliability analysis, the proposed method can get not only the entire timedependent system probability of failure curve up to a time interval of interest but also two other important outputs, namely, the timedependent probability of failure of individual components and dominant failure sequences. Three examples featuring series, parallel, and combined systems are used to demonstrate the effectiveness of the proposed method.