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

The consideration of imprecise probability in engineering analysis to account for missing,
vague or incomplete data in the description of model uncertainties is a fast-growing field of …

Active learning methods have recently surged in the literature due to their ability to solve
complex structural reliability problems within an affordable computational cost. These …

In structural reliability, an important challenge is to reduce the number of calling the
performance function, especially a finite element model in engineering problem which …

Subset Simulation is an adaptive simulation method that efficiently solves structural
reliability problems with many random variables. The method requires sampling from …

This paper presents a comprehensive review of Uncertainty-Based Multidisciplinary Design
Optimization (UMDO) theory and the state of the art in UMDO methods for aerospace …

A powerful tool in computational stochastic mechanics is the stochastic finite element
method (SFEM). SFEM is an extension of the classical deterministic FE approach to the …

Bayesian methods are a powerful tool in many areas of science and engineering, especially
statistical physics, medical sciences, electrical engineering, and information sciences. They …

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 …

The Bayesian failure probability inference (BFPI) framework provides a sound basis for
develo** new Bayesian active learning reliability analysis methods. However, it is still …