Abstract: Timedependent reliability analysis requires the use of the extreme value of a response. The extreme value function is usually highly nonlinear, and traditional reliability methods, such as the first order reliability method ...

Abstract: This paper proposes a novel and efficient methodology for timedependent system reliability analysis of systems with multiple limitstate functions of random variables, stochastic processes, and time. Since there are ...

Abstract: Maintaining high accuracy and efficiency is a challenging issue in timedependent reliability analysis. In this work, an accurate and efficient method is proposed for limitstate functions with the following features: The ...

Abstract: Current surrogate modeling methods for timedependent reliability analysis implement a doubleloop procedure, with the computation of extreme value response in the outer loop and optimization in the inner loop. The computational ...

Abstract: Significant efforts have been recently devoted to the qualitative and quantitative evaluation of resilience in engineering systems. Current resilience evaluation methods, however, have mainly focused on business supply ...

Abstract: Multidisciplinary systems with transient behavior under time-varying inputs and coupling variables pose significant computational challenges in reliability analysis. Surrogate models of individual disciplinary analyses ...

Abstract: Bayesian networks (BNs) are being studied in recent years for system diagnosis, reliability analysis, and design of complex engineered systems. In several practical applications, BNs need to be learned from available data ...

Abstract: A common strategy for the modeling of stochastic loads in time-dependent reliability analysis is to describe the loads as independent Gaussian stochastic processes. This assumption does not hold for many engineering ...

Abstract: Interval variables are commonly encountered in design, especially in the early design stages when data are limited. Thus, reliability analysis (RA) should deal with both interval and random variables and then predict the ...

Abstract: Additive manufacturing (AM) represents a new paradigm of manufacturing where parts are manufactured using their 3D models (such as CAD models) by joining materials in a layer-by-layer manner. Widespread implementation of ...