Most of the existing machine learning (ML)-based models for liquefaction assessment of
soils are black-box in nature. Database considered in the existing studies for model …

To interpret the effects of fabric anisotropy on the cyclic liquefaction of sands, undrained
cyclic triaxial tests on the vertical and horizontal specimens were simulated using the …

The formulation of a sand plasticity model for geotechnical earthquake engineering
applications is presented. The model follows the basic framework of the stress-ratio …

Majority of the presently available machine learning (ML) models employed to assess the
liquefaction potential of soils are for sands or sands containing silt fraction. In the current …

The calibration and implementation of a sand plasticity plane-strain model for geotechnical
earthquake engineering applications are presented. The constitutive model, as described by …

Numerical simulations of a centrifuge test, in which dissipation patterns, lateral spreading,
and shear strain localization were measured and recorded, are performed for validation of …

A modified flow rule has been introduced into a pressure dependent multi-yield surface
model for predicting the liquefaction of laboratory soil element tests and centrifuge …

A fully Lagrangian particle-based method for coupled fluid-particle interaction is utilized to
evaluate flow liquefaction of saturated granular soils overlain by an impermeable crust. The …

Finite-element analyses are performed of centrifuge tests consisting of untreated and drain-
treated lateral spread sites, with the goal of evaluating the ability of numerical simulations to …

Estimates of earthquake-induced deformations for geotechnical structures affected by
liquefaction can involve significant uncertainties stemming from the uncertainty in the in-situ …