Monte Carlo methods have attracted constant and even increasing attention in structural
reliability analysis with a wide variety of developments seamlessly presented over decades …

Performing time-dependent reliability analysis is an effective way to estimate the failure
probability of structural system throughout its lifetime. In the engineering practices, uncertain …

Time-dependent reliability analysis (TRA) plays an important role in improving the validity
and practicability of product reliability evaluation over an interested life interval …

Surrogate models and adaptive methods can release the huge computational burden of
structural reliability analysis. However, it is very difficult to guarantee the accuracy of …

Time-dependent reliability-based design optimization is an effective tool to guarantee a high
reliability of the product during the full life cycle. However, the necessarily repeated …

In this paper, a new single-loop active learning Kriging method with probability of rejecting
classification is proposed for solving time-dependent system reliability analysis problems …

This paper presents a long short-term memory (LSTM)-augmented deep learning framework
for time-dependent reliability analysis of dynamic systems. To capture the behavior of …

Reliability is an important tool for evaluating the performance of modern networks. Currently,
it is NP-hard and# P-hard to calculate the exact reliability of a binary-state network when the …

Time-variant reliability analysis plays a vital role in improving the validity and practicability of
product reliability evaluation over a specific time interval. Sampling-based extreme value …

The present work discusses an innovative approach to metamodeling in reliability that uses
a field-transversal rationale. Adaptive metamodeling in reliability is characterized by its large …