4.7 Article

Probabilistic assessment of seismic earth pressure against backfills with a nonlinear failure criterion

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ELSEVIER SCI LTD
DOI: 10.1016/j.soildyn.2023.108341

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Reliability analysis; Seismic earth pressure; Nonlinear failure; Optimization methods; Moment method

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This study introduces a novel approach for the probabilistic assessment of seismic earth pressure against nonlinear backfills. Nonlinear upper bound analysis is used to obtain the seismic earth pressure through optimization procedure, and probability analysis of nonlinear backfill properties is considered by combining adaptive dimension decomposition with the direct integral method.
A novel approach for the probabilistic assessment of seismic earth pressure against nonlinear backfills is introduced in this study. To implement reliability-based design for the retaining structures under seismic loading condition, nonlinear upper bound analysis is adopted to obtain the seismic earth pressure through optimization procedure. Firstly, rigorous analytical function is formulated to reveal the normal-shear stress information along the failure surface in soil with nonlinear failure criterion. Subsequently, a kinematic equation is put forward to estimate the seismic earth pressures by balancing the external work rate and the internal energy dissipation rate. The solutions are verified by the Discontinuity Layout Optimization numerical modellings based on the derived stress data from the proposed method. To consider the probability analysis of nonlinear backfill properties, the moment method is presented by combining the adaptive dimension decomposition with the direct integral method. According to the estimated first four statistical moments, the approximated probability density function of the performance function is determined contently. Finally, the failure probability of seismic earth pressure is calculated based on the proposed moment method. Two numerical examples demonstrate that the moment method can be adapted to the characteristics of nonlinear backfills and further improve the accuracy of reliability estimation by introducing higher-order moments analytically.

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