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<p>The earthquake-damaged slopes under subsequent rainfall are prone to become progressive failures, making the numerical prediction and risk management extremely challenging. Traditional non-deformation and small-deformation numerical tools cannot capture the time-dependent evolution and strain accumulation that characterize landslide processes, thereby limiting their ability to provide comprehensive insights into failure behavior. This study introduced the strain softening constitutive into the material point method (MPM) large-deformation analysis framework to predict the progressive failure of earthquake-damaged slopes under rainfall. The MPM can handle large-deformation analysis under multiphase coupling, while the strain softening constitutive model effectively captures soil strength degradation and plastic strain accumulation. The proposed method was validated through a retrogressive illustrative example and then successfully applied to the K70C slope damaged by the 2021 <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\({\text{M}}_{{\text{S}}}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mtext>M</mtext> <mtext>S</mtext> </msub> </math></EquationSource> </InlineEquation> 6.4 Yangbi earthquake. Combining the electrical measurements and geological modeling with MPM simulation, the method accurately predicts failure modes, evolution processes, and deposit topography, with results closely matching field observations and UAV surveys. The study demonstrated that MPM with strain softening constitutive modeling provides a powerful tool for numerical prediction of progressive landslides, enabling quantitative analysis of failure mechanisms and post-landslide characteristics. The method offers significant value for risk assessment and emergency response in earthquake-prone regions subjected to heavy rainfall, advancing the capability of predictive modeling in geotechnical engineering.</p>

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Numerical prediction of progressive failure in earthquake-damaged slopes under rainfall using MPM

  • 期刊论文

  • 发表日期：

    2025年10月23日

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  • Chao Su,
  • Ailan Che,
  • Ganglie Yuan,
  • Hanxu Zhou,
  • Xiaowei Li

摘要

The earthquake-damaged slopes under subsequent rainfall are prone to become progressive failures, making the numerical prediction and risk management extremely challenging. Traditional non-deformation and small-deformation numerical tools cannot capture the time-dependent evolution and strain accumulation that characterize landslide processes, thereby limiting their ability to provide comprehensive insights into failure behavior. This study introduced the strain softening constitutive into the material point method (MPM) large-deformation analysis framework to predict the progressive failure of earthquake-damaged slopes under rainfall. The MPM can handle large-deformation analysis under multiphase coupling, while the strain softening constitutive model effectively captures soil strength degradation and plastic strain accumulation. The proposed method was validated through a retrogressive illustrative example and then successfully applied to the K70C slope damaged by the 2021 \({\text{M}}_{{\text{S}}}\) M S 6.4 Yangbi earthquake. Combining the electrical measurements and geological modeling with MPM simulation, the method accurately predicts failure modes, evolution processes, and deposit topography, with results closely matching field observations and UAV surveys. The study demonstrated that MPM with strain softening constitutive modeling provides a powerful tool for numerical prediction of progressive landslides, enabling quantitative analysis of failure mechanisms and post-landslide characteristics. The method offers significant value for risk assessment and emergency response in earthquake-prone regions subjected to heavy rainfall, advancing the capability of predictive modeling in geotechnical engineering.