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Postfailure Analysis of Slopes by Random Generalized Interpolation Material Point Method
In this paper, the generalized interpolation material point (GIMP) method will be utilized to simulate the postfailure behavior of slopes that accounts for spatial variability. Because the spatial variability of soil has not been considered in the analysis of the postfailure behavior of slopes, the local average subdivision (LAS) will be used to model the spatial variability of soil properties. By combining these two methods with Monte Carlo simulation, a random generalized interpolation material point (RGIMP) method will be proposed. A homogeneous slope will first be analyzed to verify the correctness of the GIMP implementation used in this paper. Then, a strain-softening slope will be analyzed as an illustrative example to investigate the influence of the spatial variability of soil on the postfailure behavior using the RGIMP. The results show that the runout distance, the retrogression distance, and the sliding volume of the slope that considers spatial variability have significant variations compared with the homogeneous slope. In addition, the kinetic energy of the slope will be investigated. The maximum and average global kinetic energy of the slope that considers spatial variability show obvious differences compared with the homogeneous slope. According to the Pearson correlation coefficient, this shows that there were relatively strong correlations between the maximum (average) global kinetic energy and the runout distance. However, there was no apparent correlation between the maximum global kinetic energy and the retrogression distance (sliding volume).
Postfailure Analysis of Slopes by Random Generalized Interpolation Material Point Method
In this paper, the generalized interpolation material point (GIMP) method will be utilized to simulate the postfailure behavior of slopes that accounts for spatial variability. Because the spatial variability of soil has not been considered in the analysis of the postfailure behavior of slopes, the local average subdivision (LAS) will be used to model the spatial variability of soil properties. By combining these two methods with Monte Carlo simulation, a random generalized interpolation material point (RGIMP) method will be proposed. A homogeneous slope will first be analyzed to verify the correctness of the GIMP implementation used in this paper. Then, a strain-softening slope will be analyzed as an illustrative example to investigate the influence of the spatial variability of soil on the postfailure behavior using the RGIMP. The results show that the runout distance, the retrogression distance, and the sliding volume of the slope that considers spatial variability have significant variations compared with the homogeneous slope. In addition, the kinetic energy of the slope will be investigated. The maximum and average global kinetic energy of the slope that considers spatial variability show obvious differences compared with the homogeneous slope. According to the Pearson correlation coefficient, this shows that there were relatively strong correlations between the maximum (average) global kinetic energy and the runout distance. However, there was no apparent correlation between the maximum global kinetic energy and the retrogression distance (sliding volume).
Postfailure Analysis of Slopes by Random Generalized Interpolation Material Point Method
Liu, Kang (author) / Wang, Yanqiao (author) / Huang, Ming (author) / Yuan, Wei-Hai (author)
2021-01-13
Article (Journal)
Electronic Resource
Unknown
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