Reliability Analysis for Multidisciplinary Systems Involving Stationary Stochastic Processes

Abstract

The response of a component in a multidisciplinary system is affected by not only the discipline to which it belongs, but also by other disciplines of the system. If any components are subject to time-dependent uncertainties, responses of all the components and the system are also time dependent. Thus, time-dependent multidisciplinary reliability analysis is required. To extend the current time-dependent reliability analysis for a single component, this work develops a time-dependent multidisciplinary reliability method for components in a multidisciplinary system under stationary stochastic processes. The method modifies the First and Second Order Reliability Methods (FORM and SORM) so that the Multidisciplinary Analysis (MDA) is incorporated while approximating the limit-state function of the component under consideration. Then Monte Carlo simulation is used to calculate the reliability without calling the original limit-state function. Two examples are used to demonstrate and evaluate the proposed method.

Adaptive Surrogate Modeling for Time-Dependent Multidisciplinary Reliability Analysis

“…In time-independent MDRA, MDA is a deterministic analysis for a given realization of uncertainty sources, and will converge after several iterations. This situation also holds for timedependent MDRA if the time-dependent inputs only affect the system response variables but not the coupling variables [15]. However, when the time-dependent inputs affect the coupling variables, the coupling variables will change over time; thus we do not have distributions of converged values of these coupling variables and will not be able to decouple the disciplinary analyses.…”

“…These methods, however, are developed for single disciplinary systems and cannot be directly applied to multidisciplinary systems, due to the complicated couplings between different disciplinary simulations. Motivated by solving this problem, Zhu et al [15] recently developed a time-dependent reliability analysis method for a multidisciplinary system using the first-order reliability method (FORM). Since FORM could have large errors for problems with nonlinear limit-state functions, the method presented in Ref.…”

“…Since FORM could have large errors for problems with nonlinear limit-state functions, the method presented in Ref. [15] can only be applied to multidisciplinary systems where FORM is accurate [15].…”

System Reliability Analysis With Autocorrelated Kriging Predictions

“…In general, system reliability methods are classified into two major groups: analytical methods and sampling-based methods. The most popular analytical methods are the First and Second Order Reliability Methods (FORM and SORM) [3][4][5][6], which employ a first and second order approximation, respectively, to a limit-state function in the vicinity of the Most Probable Point (MPP). But for limit-state functions that are not linear or quadratic, significant errors could be introduced by FORM and SORM.…”