Journal
ACTA GEOTECHNICA
Volume -, Issue -, Pages -Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s11440-023-02138-2
Keywords
Dimensionality reduction; Efficient slope reliability analysis; Multivariate adaptive regression splines; Response conditioning method; Spatial variability; Subset simulation
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In this study, an efficient numerical-simulation-based slope reliability analysis (NSB-SRA) method considering spatial variability is proposed. By employing dual dimensionality reduction and response conditioning techniques, the computational time is reduced and the accuracy of slope reliability assessment is improved.
Currently, numerical-simulation-based slope reliability analysis (NSB-SRA) considering spatial variability is still a time-consuming task. To address this problem, this study proposed an efficient numerical-simulation-based slope reliability analysis method. Dual dimensionality reduction technique is firstly employed to greatly reduce random variables that are required for establishing a limit-equilibrium-analysis-based multivariate adaptive regression splines (MARS) model. Then, response conditioning method is used to select the failure samples predicted by MARS model as samples for performing NSB-SRA. Finally, the proposed method is validated through two spatially variable slope examples. The results show that MARS + FDM is an efficient solution to perform NSB-SRA, especially for low-probability-level NSB-SRA problem. Besides, NSB-SRA is necessary for cases of horizontal scale of fluctuation, smaller vertical of fluctuation, larger variability of undrained shear strength, and stronger positive cross-correlation between cohesion and internal friction angle because neglecting NSB-SRA will lead to an unreliable assessment on slope reliability.
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