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An adaptive sampling approach to reduce uncertainty in slope stability analysis.

Authors :
Cai, Jing-Sen
Yeh, Tian-Chyi Jim
Yan, E-Chuan
Tang, Rui-Xuan
Wen, Jet-Chau
Huang, Shao-Yang
Source :
Landslides; Jun2018, Vol. 15 Issue 6, p1193-1204, 12p
Publication Year :
2018

Abstract

An adaptive sampling approach is proposed, which can sample spatially varying shear strength parameters efficiently to reduce uncertainty in the slope stability analysis. This approach employs a limit equilibrium model and stochastic conditional methodology to determine the likely sampling locations. Karhunen-Loève expansion is used to conduct the conditional Monte Carlo simulation. A first-order analysis is also proposed to ease the computational burden associated with Monte Carlo simulation. These approaches are then tested using borehole data from a field site. Results indicate that the proposed adaptive sampling approach is an effective and efficient sampling scheme for reducing uncertainty in slope stability analysis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1612510X
Volume :
15
Issue :
6
Database :
Complementary Index
Journal :
Landslides
Publication Type :
Academic Journal
Accession number :
129593798
Full Text :
https://doi.org/10.1007/s10346-017-0936-2