Spatial variability of soil properties was rarely taken into account directly in traditional slope
stability analyses, rather some “average” or suitably “pessimistic” properties are assumed to …

Particle shape affects the mechanical properties of sands, but the underlying micro-
mechanisms are not yet explored, at least partially, due to difficulties in accessing the …

Recently, random field copulas have been deployed to characterise the dependent
structures of spatially variable soil parameters. This study expands on this concept by …

In natural slopes, apart from isotropic and transversely anisotropic soil fabric, rotated
anisotropic soil fabric is also commonly observed due to deposition and weathering …

Soil properties are known to have high spatial variability and often fluctuate with depth. The
objective of this study was to investigate the effects of using different models to simulate the …

Abstract Geographically Weighted Principal Component Analysis (GWPCA) is an extension
of classical PCA to deal with the spatial heterogeneity of geographical data. This …

Material properties, crucial design parameters in landfill cover systems, can exhibit spatial
variability due to non-uniform particle size and uneven compaction, affecting cover …

Multivariate distribution models for geo-material parametric data play a crucial role in
reliability-based design. Currently, two major models are commonly used: the conventional …

For improving the reliability analysis of bridge girders, a consideration of the nonlinear
dependence among multivariable random variables is essential. Thus, this study presents a …

The Newmark-type predictive models are extensively used to estimate earthquake-induced
sliding displacements (D) of slopes. Most existing models are designed for shallow slope …