Please use this identifier to cite or link to this item: https://doi.org/10.1002/nag.1112
Title: Bivariate simulation using copula and its application to probabilistic pile settlement analysis
Authors: Li, D.-Q.
Tang, X.-S.
Phoon, K.-K. 
Chen, Y.-F.
Zhou, C.-B.
Keywords: Copula
Joint probability distribution
Kendall rank correlation coefficient
Load-displacement curve
Pearson correlation coefficient
Piles
Probability of failure
Issue Date: 25-Apr-2013
Source: Li, D.-Q., Tang, X.-S., Phoon, K.-K., Chen, Y.-F., Zhou, C.-B. (2013-04-25). Bivariate simulation using copula and its application to probabilistic pile settlement analysis. International Journal for Numerical and Analytical Methods in Geomechanics 37 (6) : 597-617. ScholarBank@NUS Repository. https://doi.org/10.1002/nag.1112
Abstract: This paper aims to propose a procedure for modeling the joint probability distribution of bivariate uncertain data with a nonlinear dependence structure. First, the concept of dependence measures is briefly introduced. Then, both the Akaike Information Criterion and the Bayesian Information Criterion are adopted for identifying the best-fit copula. Thereafter, simulation of copulas and bivariate distributions based on Monte Carlo simulation are presented. Practical application for serviceability limit state reliability analysis of piles is conducted. Finally, four load-test datasets of load-displacement curves of piles are used to illustrate the proposed procedure. The results indicate that the proposed copula-based procedure can model and simulate the bivariate probability distribution of two curve-fitting parameters underlying the load-displacement models of piles in a more general way. The simulated load-displacement curves using the proposed procedure are found to be in good agreement with the measured results. In most cases, the Gaussian copula, often adopted out of expedience without proper validation, is not the best-fit copula for modeling the dependence structure underlying two curve-fitting parameters. The conditional probability density functions obtained from the Gaussian copula differ considerably from those obtained from the best-fit copula. The probabilities of failure associated with the Gaussian copula are significantly smaller than the reference solutions, which are very unconservative for pile safety assessment. If the strong negative correlation between the two curve-fitting parameters is ignored, the scatter in the measured load-displacement curves cannot be simulated properly, and the probabilities of failure will be highly overestimated. © 2011 John Wiley & Sons, Ltd.
Source Title: International Journal for Numerical and Analytical Methods in Geomechanics
URI: http://scholarbank.nus.edu.sg/handle/10635/58969
ISSN: 03639061
DOI: 10.1002/nag.1112
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