Abstract: A methodology to account for the effect of epistemic uncertainty (regarding model parameters) on the strength prediction of carbon fiber reinforced polymer (CFRP) composite laminates is presented. A three-dimensional ...

Abstract: Model calibration and validation are two activities in system model development, and both of them make use of test data. Limited testing budget creates the challenge of test resource allocation, i.e., how to optimize the ...

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: 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: In a Bayesian network (BN), how a node of interest is affected by the observation at another node is a main concern, especially in backward inference. This challenge necessitates the proposed global sensitivity analysis ...

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: This study investigates the use of big data analytics in uncertainty quantification and applies the proposed framework to structural diagnosis and prognosis. With smart sensor technology making progress and low-cost online ...