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Efficient numerical-simulation-based slope reliability analysis considering spatial variability
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.
Efficient numerical-simulation-based slope reliability analysis considering spatial variability
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.
Efficient numerical-simulation-based slope reliability analysis considering spatial variability
Acta Geotech.
Chen, Longlong (Autor:in) / Zhang, Wengang (Autor:in) / Paneiro, Gustavo (Autor:in) / He, Yuwei (Autor:in) / Hong, Li (Autor:in)
Acta Geotechnica ; 19 ; 2691-2713
01.05.2024
23 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Dimensionality reduction , Efficient slope reliability analysis , Multivariate adaptive regression splines , Response conditioning method , Spatial variability , Subset simulation Engineering , Geoengineering, Foundations, Hydraulics , Solid Mechanics , Geotechnical Engineering & Applied Earth Sciences , Soil Science & Conservation , Soft and Granular Matter, Complex Fluids and Microfluidics
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