Machine Learning Aided Reliability Analysis for Spatially Varying Slopes in 2D and 3D

The Random Finite Element Method (RFEM) is a robust stochastic method for slope reliability analysis that incorporates the spatial variability of soil properties. However, the extensive computational time associated with the direct Monte Carlo simulation limits its practical application. To overcome this problem, this study investigates the use...

Surrogate modelling framework for probabilistic assessment of slope stability of dikes on heterogeneous soils

Climatic conditions in uence peak discharges in rivers and change sea levels; therefore, attention to the safety of dikes is of ever growing importance. Macro instability is one of the dike failure mechanisms that can inundate the hinterland. Soil heterogeneity plays an important role in assessing dike safety, especially for slope stability,...

Automated assessment of slope stability: Application of machine learning to ERT monitoring data andintegration with geomechanical models

Landslides pose a risks to the communities settled in their vicinity. They pose a threat to human lives and significant economical damage to the affected communities. As the scientific community agrees that the climate change will further increase the risks associated with landslides, it is important to develop a reliable, cost effective and...