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<p>This study focused on investigating the bearing capacity and failure mechanisms of circular foundations placed adjacent to <i>c</i>-<i>φ</i> soil slopes under horizontal seismic effects. The problem was directly addressed using a numerical approach based on the three-dimensional Finite Element Limit Analysis (3D FELA). The input parameters considered in this analysis include slope angle, setback ratio, embedment ratio, normalized cohesion, internal friction angle, and horizontal seismic coefficient. The results showed that all the investigated parameters influenced both the bearing capacity and failure mechanism of the soil. A deep learning model combining a Deep Neural Network and Firefighter Optimizer was proposed to predict the bearing capacity for cases not analyzed by 3D FELA. The proposed model demonstrated very high prediction accuracy, with the coefficient of determination in training of 0.9948 and testing of 0.9939. This paper successfully proposed a comprehensive approach to accurately investigate the behavior of circular foundations on slopes under seismic effects.</p>

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The Bearing Capacity of Circular Shallow Foundation Resting on Cohesive-Frictional Slopes Considering Seismic Effects

  • 期刊论文

  • 发表日期：

    2026年4月1日

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  • Hoang Nghi Le,
  • Huu Nghia Bui,
  • Duy Tan Tran,
  • Trong Nghia Le,
  • Van Qui Lai

摘要

This study focused on investigating the bearing capacity and failure mechanisms of circular foundations placed adjacent to c-φ soil slopes under horizontal seismic effects. The problem was directly addressed using a numerical approach based on the three-dimensional Finite Element Limit Analysis (3D FELA). The input parameters considered in this analysis include slope angle, setback ratio, embedment ratio, normalized cohesion, internal friction angle, and horizontal seismic coefficient. The results showed that all the investigated parameters influenced both the bearing capacity and failure mechanism of the soil. A deep learning model combining a Deep Neural Network and Firefighter Optimizer was proposed to predict the bearing capacity for cases not analyzed by 3D FELA. The proposed model demonstrated very high prediction accuracy, with the coefficient of determination in training of 0.9948 and testing of 0.9939. This paper successfully proposed a comprehensive approach to accurately investigate the behavior of circular foundations on slopes under seismic effects.