This study provides a comprehensive analysis of the undrained failure envelope for spudcan foundations in anisotropic clays using the AUS failure criterion as the soil strength model. The influence of embedment depth (L/D) and anisotropic strength (re) on spudcan behaviour under combined loading conditions is investigated. Failure envelopes are derived through three-dimensional finite element limit analysis (3D FELA) in both (H/ suTCA, M/suTCAD) and (V/Vult, H/suTCA, M/suTCAD) spaces. The study also illustrates spudcan foundation failure mechanisms, providing valuable insights for designing footings in anisotropic clays under combined loads (V, H, M). Additionally, an innovative soft-computing approach is introduced: a machine learning model that integrates categorical boosting (CatBoost) with the flower pollination algorithm (FPA) for optimized predictions of the spudcan failure envelope. The proposed FPA-CatBoost model is validated against numerical FELA results, demonstrating a strong correlation and offering engineers a reliable tool for determining spudcan foundation failure envelopes under varied loading conditions.
