Abstract
(1) Background: in practical applications, probabilistic and non-probabilistic information often simultaneously exit. For a complex system with a nonlinear limit-state function, the analysis and evaluation of the reliability are imperative yet challenging tasks. (2) Methods: an improved second-order method is proposed for reliability analysis in the presence of both random and interval variables, where a novel polar transformation is employed. This method enables a unified reliability analysis taking both random variables and bounded intervals into account, simplifying the calculation by transforming a high-dimension limit-state function into a bivariate state function. The obtained nonlinear probability density functions of two variables in the function inherit the statistic characteristics of interval and random variables. The proposed method does not require any strong assumptions and so it can be used in various practical engineering applications. (3) Results: the proposed method is validated via two numerical examples. A comparative study towards a contemporary algorithm in state-of-the-art literature is carried out to demonstrate the benefits of our method. (4) Conclusions: the proposed method outperforms existing methods both in efficiency and accuracy, especially for cases with strong nonlinearity.
Highlights
In recent years the influences of uncertainty on dimensions, geometries, material properties, and load have become more and more profound
Structural reliability is typically estimated by the probability of failure (POF) and the reliability index based on the probability theory [5,6,7,8]
This paper proposes the use of the uncertain-polar coordinates second-order reliability method (SORM) (UPSORM) that handles random and interval hybrid variables, significantly reducing computational complexity while achieving comparable precision
Summary
Abstract: (1) Background: in practical applications, probabilistic and non-probabilistic information often simultaneously exit. (2) Methods: an improved second-order method is proposed for reliability analysis in the presence of both random and interval variables, where a novel polar transformation is employed. For a complex system with a nonlinear limit-state function, the analysis and evaluation of the reliability are imperative yet challenging tasks. This method enables a unified reliability analysis taking both random variables and bounded intervals into account, simplifying the calculation by transforming a high-dimension limit-state function into a bivariate state function. The proposed method does not require any strong assumptions and so it can be used in various practical engineering applications.
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