Stochastic response surface method for reliability analysis of rock slopes involving correlated non-normal variables

By Dianqing Li, Yi‐Feng Chen, Wenbo Lu, Chuangbing Zhou. 2011

314 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/8f444b63eec273bb1095e5717a76658a9bbf6c47

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In Civil and Structural Engineering

In Safety, Risk, Reliability and Quality

In Statistics and Probability

Citations in the corpus

Influence of rock property correlation on reliability analysis of rock slope stability: From property characterization to reliability analysis (2017, background): “Whilemany investigators have contributed to the subject of reliability or failure probability of rock slopes (e.g., Park and West, 2001; Duzgun et al., 2003; Hoek, 2007; Low, 2007; Duzgun and Bhasin, 2009; Li et al., 2011; Lee et al., 2012), effort has not been directed towards quantification of the”
A sequential sparse polynomial chaos expansion using Bayesian regression for geotechnical reliability estimations (2020, methodology): “To the authors' best knowledge, in previously published articles related to PCEs, the training samples are selected either randomly or only considering the uniformity of samples.(12,14,17,24) The method of sequentially selecting informative samples to enrich training samples has rarely been reported”
Slope reliability analysis considering spatially variable shear strength parameters using a non-intrusive stochastic finite element method (2014, methodology): “To obtain the random field realizations of spatially variable cu, an independent standard normal sample matrix ξ with dimensions of 10 × 66 is first generated for the 2nd order Hermite PCE using the probabilistic collocation points (e.g., Li et al., 2011).”
Efficient reliability method for implicit limit state surface with correlated non‐Gaussian variables (2015, methodology): “RSM aims at approximating the actual LSS using closed-form expressions by simple polynomials [3–6], Hermite polynomial chaos expansion [7, 8], neural networks [9–11], and support vector machines [12–14].”
Improved knowledge-based clustered partitioning approach and its application to slope reliability analysis (2012, methodology): “Furthermore, these parameters usually follow non-normal distributions [2,33,17,19].”
Bivariate distribution models using copulas for reliability analysis (2013, background): “Based on equation (5) and equation (19), one can obtain”
A multiple response-surface method for slope reliability analysis considering spatial variability of soil properties (2015, methodology): “As an alternative, the response surface method (RSM) has been widely applied to slope reliability problems (e.g., Li et al., 2011, 2013b; Jiang et al., 2014a).”
Copula-based approaches for evaluating slope reliability under incomplete probability information (2015, unknown): “[16] investigated the rock slope reliability involving correlated non-normal variables using Nataf distribution.”
Bearing capacity of strip footings on spatially random soils using sparse polynomial chaos expansion (2011, unknown): “[11]; Mollon et al .”
Response surface methods for slope reliability analysis: Review and comparison (2016, methodology): “If spatial variability of soil properties is not considered, NMC random variable samples X are obtained using the Nataf transformation (e.g., Lebrun and Dutfoy, 2009; Li et al., 2011; Tang et al., 2013).”
Bivariate simulation using copula and its application to probabilistic pile settlement analysis (2013, background): “INTRODUCTION The geotechnical engineering literature is replete with correlations between two engineering parameters, for example, undrained shear strength and cone tip resistance, negative correlation between cohesion and friction angle [1,2], two hyperbolic curve-fitting parameters underlying load”