Bivariate simulation using copula and its application to probabilistic pile settlement analysis

By Dianqing Li, Xiao-Song Tang, Kok-Kwang Phoon, Yi‐Feng Chen, Chuangbing Zhou. 2013

139 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/0a2a16a106035b108e731e8a583913c213952cb2

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In Civil and Structural Engineering

In Safety, Risk, Reliability and Quality

In Statistics and Probability

Citations in the corpus

Improved knowledge-based clustered partitioning approach and its application to slope reliability analysis (2012, background): “Furthermore, these parameters usually follow non-normal distributions [2,33,17,19].”
Bivariate distribution models using copulas for reliability analysis (2013, methodology): “504 Proc IMechE Part O: J Risk and Reliability 227(5)”
Slope reliability analysis considering spatially variable shear strength parameters using a non-intrusive stochastic finite element method (2014, methodology): “…for the 3rd order PCE as the “exact” solution, the relative error in reliability index for the 2nd order PCE is below 5.0%, which indicates that the 2nd order PCE has converged and canproduce satisfactory results based on the convergence property of the PCE (Mollon et al., 2011; Li et al., 2013a).”
Impact of sample size on geotechnical probabilistic model identification (2017, methodology): “The two curve-fitting parameters in a loadsettlement curve of piles [9,16,17,12], and curve-fitting parameters in a soil-water characteristic curve [26] also have a strongly negative correlation.”
Impact of copulas for modeling bivariate distributions on system reliability (2013, methodology): “[19], the Nataf model essentially adopts a Gaussian copula for modeling the dependence structure among the variables.”
Copula-based approaches for evaluating slope reliability under incomplete probability information (2015, unknown): “, N}, the Akaike Information Criterion (AIC) [2] is often used to identify the best-fit copula between c and tan/ [19, 32].”
Performance of translation approach for modeling correlated non-normal variables (2012, background): “It is well accepted that the modeling and simulation of non-Gaussian random vectors are challenging problems [6,7].”
Characterization of uncertainty in probabilistic model using bootstrap method and its application to reliability of piles (2015, background): “[14] pointed out that the translation approach essentially adopts a Gaussian copula for modeling the dependence between a and b.”