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The Probability and Sensitivity Analysis of Slope Stability Under Seepage Based on Reliability Theory

Abstract

In order to compensate the deficiency that uses the safety factor as the sole criterion to measure the stability of the tailings pond, based on the Monte Carlo test principle and the field investigation, a probability and sensitivity considering the spatial variability of reservoir sand layers were analyzed by a finite element analysis method. The results showed that the different sampling methods made the instability probability and reliability index fluctuate greatly, but they did not make the safety coefficient change obviously, which can also provide the range of instability probability and reliability index. In addition, it also proved that the probability analysis can reflect the actual coupling of water and soil in the tailings pond, and it was not appropriate to use the safety factor as the sole criterion to measure its stability. The sensitivity analysis also showed the sensitivity of the main parameters of the sand layer to the safety factor, and indicated that the change of its natural density would not make the tailings destabilizing, while the cohesion was the main sand sensitivity factor that affects its stability. The study provided a theoretical basis for the operation and management of the tailings pond in the future with certain guiding significance.

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Acknowledgements

The study was funded by the Major basic research project of Shaanxi provincial science and technology department (2016ZDJC-21), Key projects of Shaanxi science and technology bureau (2018GY-099, S2018-YF-YBGY- 0149), Scientific research projects of Shaanxi education department (18JK0248), Shangluo science and technology bureau project (SK2016-50).

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Correspondence to Tao Li.

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Li, T., Liu, G., Wang, C. et al. The Probability and Sensitivity Analysis of Slope Stability Under Seepage Based on Reliability Theory. Geotech Geol Eng (2020). https://doi.org/10.1007/s10706-020-01226-4

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Keywords

  • Tailings pond
  • Monte Carlo test
  • Probability analysis
  • Sensitivity analysis