Effects of uncertainties in the particle distribution of rubber-soil mixture on the performance of shallow foundations

Modeling granular materials is essential for understanding their complex mechanical behaviors, particularly in soil-structure interaction (SSI), where factors like particle size, material properties, and boundary conditions influence structural response.Accurate SSI modeling is critical for geotechnical engineering applications, yet uncertainties in soil properties can significantly affect load distribution, deformation, and structural response.This study employs the open-source Discrete Element Method (DEM) software YADE (Yet Another Dynamic Engine) to analyze SSI dynamics, incorporating particle shape variability, contact models, and coupling with other numerical methods.A key challenge in DEM simulations is the inherent uncertainty in particle packing, arising from random placement, particle size distribution deviations, and densification methods.To assess these uncertainties, a Monte Carlo approach is proposed to evaluate how variability in granulometric properties affects SSI parameters under different soil condition, namely: sand and rubber-soil mixtures-a material widely used in geotechnical seismic isolation (GSI) due to its unique deformablegranular behavior.The study investigates the impact of random particle distributions on critical SSI parameters, including lateral and rotational stiffness of shallow foundations, providing insights into uncertainty propagation and improving predictive accuracy for engineering design.