Modeling only constitutes one aspect of decision making. The prevailing limitation of
applying modeling to practice is the absence of explicit consideration of uncertainties. This …

This article presents a brief survey on some of the latest developments in the area of
reliability-based design optimization of structural systems under stochastic excitation. The …

Neural networks (NNs) are currently changing the computational paradigm on how to
combine data with mathematical laws in physics and engineering in a profound way …

Reliability analysis approach provides a rational means to quantitatively evaluate the safety
of geotechnical structures from a probabilistic perspective. However, it suffers from a known …

Random finite element method (RFEM) provides a rigorous tool to incorporate spatial
variability of soil properties into reliability analysis and risk assessment of slope stability …

A novel methodology that involves the coupling of Convolutional Neural Networks (CNNs)
and a data augmentation technique is proposed for slope reliability calculations. The …

This paper proposes the application of sequential importance sampling (SIS) to the
estimation of the probability of failure in structural reliability. SIS was developed originally in …

This paper proposes an efficient Kriging-based subset simulation (KSS) method for hybrid
reliability analysis under random and interval variables (HRA-RI) with small failure …

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

In this paper, the adaptive importance sampling (AIS) method is extended for hybrid
reliability analysis under random and interval variables (HRA-RI) with small failure …