The welding of steel generates substantial welding residual stress (WRS), which exerts a
significant impact on the fatigue life of steel bridges. In this study, a physical model for …

The Bayesian failure probability inference (BFPI) framework provides a well-established
Bayesian approach to quantifying our epistemic uncertainty about the failure probability …

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

Efficiency is an important issue in structural reliability analysis. In this paper, a novel method
is proposed to increase the efficiency of Monte Carlo Simulation by means of a machine …

The well-established Bayesian failure probability inference (BFPI) framework offers a solid
foundation for developing new Bayesian active learning reliability analysis methods …

Predicting the expected lifetime of structural systems is fundamental for effective design and
maintenance. However, existing methods based on physics overlook critical spatial …

Investigating the relationship between temperature variations and bridge bearing
displacement is crucial for ensuring structural integrity and safety. However, the current …

In engineering practices, it is a time-consuming procedure to estimate the small failure
probability of highly nonlinear and dimensional limit state functions and Kriging-based …

The concept of Bayesian active learning has recently been introduced from machine
learning to structural reliability analysis. Although several specific methods have been …

Numerical simulation technology is a crucial tool for reducing costs and increasing efficiency
in the wind power industry. However, with the development of large-scale wind turbines, the …