Coupled Finite Element Analysis and Multivariate Adaptive Regression Splines for predicting the bearing capacity of conical footings on slopes

Abstract Exploring the behavior of conical footings is a significant aspect of geotechnical engineering, particularly in supporting wind turbine towers on mountain slopes. This study employs Finite Element Analysis (FEA) within Plaxis 3D to investigate the behavior of conical footings. The Mohr-Coulomb material is assumed, and the research focuses on two pivotal parameters of soil shear strength: c (cohesion) and φ (friction angle). The study aims to assess the impacts of geometry parameters, consisting of the conical angle ( α ), the setback ratio ( b/B ), and the slope angle ( β ), on the failure mechanisms of conical footing. Furthermore, Multivariate Adaptive Regression Splines (MARS) models are implemented with the FEA dataset to propose a predictive formula of the UBC (ultimate bearing capacity) factor, indicating the relationship between these five input parameters and the outcome UBC. A sensitivity analysis was also examined, revealing the contribution of each variable to the UBC of conical footings on slopes.