Estimation of Small Time-Dependent Failure Probability in High Dimensions using Subset Simulation

Abstract

Time-dependent reliability analysis of deteriorating structures is significant in their performance assessment and maintenance. Various methodologies have been used by researchers to predict the time-dependent reliability of structures. However, it is still a challenge to estimate the small time-dependent failure probability in high dimensions. In the present study, based on subset simulation an adaptive stochastic simulation procedure is proposed considering the stochastic nature of the occurrence of time-dependent random variables. Moreover, a modified Metropolis-Hastings algorithm is developed to reduce repeated trajectories and suit the property of time-dependent reliability problem. Fourth-moment transformation is utilized in the study for without the exclusion of random variables with unknown probability distributions. The proposed method is illustrated by a cantilever tube subjected to external forces and torsion. The methodology can be used as a tool for structural engineers and asset managers to assess small time-dependent failure probability of a deteriorating structure in high dimensions and make decisions with regard to its maintenance and rehabilitation.