Probabilistic Assessment of Slope Stability That Considers the Spatial Variability of Soil Properties

By Sung-Eun Cho. 2010

418 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/4f247ef82366b37a48208d8901199787558623c7

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In Civil and Structural Engineering

In Safety, Risk, Reliability and Quality

Citations in the corpus

Probabilistic analysis of simple slopes with cohesive soil strength using RLEM and RFEM (2017, methodology): “…can suffer from excessive computational effort since the strength reduction method calculates the factor of safety by progressively reducing or increasing the shear strength of the soil at each mesh element in order to bring the slope to a state of limiting equilibrium (Cho 2010; Chok et al. 2016).”
Slope reliability analysis considering spatially variable shear strength parameters using a non-intrusive stochastic finite element method (2014, methodology): “The cohesion and friction angle, often used for slope reliability analysis, are considered to be negatively correlated (e.g., Lumb, 1970; Wolff, 1985; Cho, 2010; Tang et al., 2013).”
A multiple response-surface method for slope reliability analysis considering spatial variability of soil properties (2015, methodology): “Direct Monte Carlo Simulation (MCS) is a conceptually simple and robust tool for analyzing the reliability of slopes in spatially variable soils (Cho, 2010; Huang et al., 2010; Wang et al., 2011; Li et al., 2013a, 2014).”
System reliability analysis of soil nail wall using random finite element method (2020, methodology): “The soil parameter fluctuation for natural soil slope stability in conjunction with LEM has been utilized by Vanmarcke (1980), ElRamly et al. (2002), Cho (2009), Li et al. (2015), and Javankhoshdel et al. (2017).”
Probabilistic analysis of strip footings resting on a spatially random soil using subset simulation approach (2012, background): “For a lognormal random field, Equation ( 1 ) becomes (Cho 2010 , Cho and Park 2010 ):”
Determining the Factors of Safety of Spatially Variable Slopes Modeled by Random Fields (2013, methodology): “Spatial variability as a main source of uncertainty in slopes has recently been widely incorporated into slope reliability analyses (e.g., Griffiths and Fenton 2004; Griffiths et al. 2009; Cho 2010; Huang et al. 2010).”
Response surface methods for slope reliability analysis: Review and comparison (2016, methodology): “To constructNs surrogate performance functions between FS values of all the potential slip surfaces and the input parameters ξ when spatial variability of soil properties is considered, Np realizations of independent or cross-correlated random fields are generated using the Karhunen–Loève expansion ”