In traditional slope stability analysis, it is assumed that some “average” or appropriately
“conservative” properties operate over the entire region of interest. This kind of deterministic …

Abstract Random field Monte Carlo (MC) reliability analysis is a robust stochastic method to
determine the probability of failure. This method, however, requires a large number of …

The maintenance of safety and dependability in rail and road embankments is of utmost
importance in order to facilitate the smooth operation of transportation networks. This study …

The use of probabilistic analysis (PA) of slopes as an effective method for evaluating the
uncertainty that is so pervasive in variables has become increasingly common in recent …

Landslide-induced river damming poses a considerable threat to the safety of humans and
infrastructure. Prediction of landslide-induced river damming is of great significance for …

Landslides, one of the most common mountain hazards, can result in enormous casualties
and huge economic losses in mountainous regions. In order to address the landslide …

Surrogate models are often used to alleviate extensive computational burden for slope
reliability analysis. How to efficiently train a surrogate model with high precision is always a …

This study presented a probabilistic assessment of heavy-haul railway track using a high-
performance computational model called multi-gene genetic programming (MGGP). A …

Quantifying building vulnerability under landslide run-out impacts is a pivotal aspect of
landslide quantitative risk assessment (QRA). The degree of loss of buildings exposed to …

It is still a challenging task to implement efficient methods for reliability analysis, especially
for complex engineering systems that have implicit limit state surfaces and multiple failure …