Time-Dependent Reliability Analysis for Bivariate Responses
Time-dependent system reliability is measured by the probability that the responses of a system do not exceed prescribed failure thresholds over a period of time. In this work, an efficient time-dependent reliability analysis method is developed for bivariate responses that are general functions of random variables and stochastic processes. The proposed method is based on single and joint upcrossing rates, which are calculated by the First Order Reliability Method (FORM). The method can efficiently produce accurate upcrossing rates for the systems with two responses. The upcrossing rates can then be used for system reliability predictions with two responses. As the general system reliability may be approximated with the results from reliability analyses for individual responses and bivariate responses, the proposed method can be extended to reliability analysis for general systems with more than two responses. Two examples, including a parallel system and a series system, are presented.
Z. Hu et al., "Time-Dependent Reliability Analysis for Bivariate Responses," Proceedings of the ASME 2015 International Mechanical Engineering Congress and Exposition (2015, Houston, TX), vol. 14-2015, American Society of Mechanical Engineers (ASME), Nov 2015.
The definitive version is available at https://doi.org/10.1115/IMECE2015-53441
ASME 2015 International Mechanical Engineering Congress and Exposition (2015: Nov. 13-19, Houston, TX)
Mechanical and Aerospace Engineering
Keywords and Phrases
Random processes; Reliability; Risk analysis; Risk assessment; Safety engineering; Stochastic systems; Structural analysis; Bivariate response; Failure thresholds; First order reliability methods; General functions; General systems; System reliability; Time dependent reliability analysis; Time-dependent systems; Reliability analysis
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2015 American Society of Mechanical Engineers (ASME), All rights reserved.
01 Nov 2015