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    Volume 50 Issue 10
    Oct.  2025
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    Liang Yaoying, Peng Ming, Liu Liu, Shi Zhenming, Wang Dengyi, Shen Jian, 2025. System Reliability Analysis of Multi-Slip Surface Slopes Based on Geological Structure Detection. Earth Science, 50(10): 3982-3996. doi: 10.3799/dqkx.2025.063
    Citation: Liang Yaoying, Peng Ming, Liu Liu, Shi Zhenming, Wang Dengyi, Shen Jian, 2025. System Reliability Analysis of Multi-Slip Surface Slopes Based on Geological Structure Detection. Earth Science, 50(10): 3982-3996. doi: 10.3799/dqkx.2025.063

    System Reliability Analysis of Multi-Slip Surface Slopes Based on Geological Structure Detection

    doi: 10.3799/dqkx.2025.063
    • Received Date: 2024-12-29
    • Publish Date: 2025-10-25
    • The identification of geological structures and the quantification of uncertainties in strength parameters are crucial for assessing the stability of rock slopes. This study proposes a system reliability analysis method for multi-slip surface slopes based on geological structure detection. The method integrates multichannel analysis of Love waves (MALW) and first-arrival travel time tomography (FATT) to achieve complementary detection of weak layers and faults. Elastic wave velocities are used to reduce the strength parameters of weak layers, and their probabilistic distributions are statistically derived. By incorporating parameter uncertainties, the surface displacement of slopes and the failure probabilities of individual slip surfaces and the entire system are calculated. Case studies indicate that multi-mode dispersion curves achieve higher inversion accuracy for both deep and shallow weak layers compared to fundamental-mode dispersion curves, and Love waves are less affected by undulations at rock layer interfaces than Rayleigh waves. Slope faults exhibit characteristic wave fluctuations within specific ranges in first-arrival travel time records. Inversion based on these features enables the localization of local faults.In the case of multi-slip surface slopes, deep slip surfaces are identified as the primary controlling factor, and the system failure probability is more significantly affected by the coefficient of variation of the internal friction angle than by cohesion. This method effectively detects geological structures, locates weak layers and faults, and quantifies uncertainties in strength parameters, providing a scientific basis for slope stability analysis and mitigation measures.

       

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