Reliability Analysis for Multidisciplinary Systems with Random and Interval Variables

Abstract

Tremendous efforts have been devoted to developing efficient approaches to reliability analysis for multidisciplinary systems. Most of the approaches are only capable of dealing with random variables modeled by probability distributions. Both random and interval variables, however, may exist in multidisciplinary systems. Their propagation through coupled subsystems make s reliability analysis computationally expensive. In this work, a unified reliability analysis framework is proposed to deal with both random and interval variables in multidisciplinary systems. The framework is an extension of an existing unified uncertainty analysis framework for single-disciplinary problems. The new framework involves probabilistic analysis and interval analysis. Both probabilistic analysis and interval analysis are decoupled from each other and are performed sequentially. The first order reliability method is used for probabilistic analysis. Three supporting algorithms are developed. The effectiveness of the algorithms is demonstrated with a mathematical example and an engineering application.