Time-dependent mechanism reliability analysis with imprecise probability distributions based on envelope function

The time-dependent mechanism reliability and sensitivity analysis with imprecise probability distributions is investigated in this article. First, the interval model is employed to describe the uncertainty of the parameters of input variables due to the lack of data and knowledge. Next, the form of time-dependent failure probability and global reliability sensitivity (GRS) main effect index in the case of interval distribution parameters is analyzed. Then, the calculation methods of failure probability and GRS main effect index under the above circumstance are discussed. Finally, combined with the optimization algorithm, the Monte Carlo simulation (MCS) method and the method based on envelope function (MEVF) are proposed. By comparing with the MCS results, several numerical and engineering examples are analyzed to demonstrate the significance as well as the effectiveness of MEVF.

Automated summary

This article investigates the time-dependent mechanism reliability and sensitivity analysis with imprecise probability distributions. The interval model is employed to describe the uncertainty of the parameters of input variables, and the form of time-dependent failure probability and global reliability sensitivity (GRS) main effect index is analyzed. Calculation methods of failure probability and GRS main effect index are discussed, and the Monte Carlo simulation (MCS) method and the method based on envelope function (MEVF) are proposed. Several numerical and engineering examples are analyzed to demonstrate the significance and effectiveness of MEVF.