Determining the joint probability distribution of correlated non-normal geotechnical parameters based on incomplete statistical data is a challenging problem.This paper proposes a Gaussian copula-based method for mode...Determining the joint probability distribution of correlated non-normal geotechnical parameters based on incomplete statistical data is a challenging problem.This paper proposes a Gaussian copula-based method for modelling the joint probability distribution of bivariate uncertain data.First,the concepts of Pearson and Kendall correlation coefficients are presented,and the copula theory is briefly introduced.Thereafter,a Pearson method and a Kendall method are developed to determine the copula parameter underlying Gaussian copula.Second,these two methods are compared in computational efficiency,applicability,and capability of fitting data.Finally,four load-test datasets of load-displacement curves of piles are used to illustrate the proposed method.The results indicate that the proposed Gaussian copula-based method can not only characterize the correlation between geotechnical parameters,but also construct the joint probability distribution function of correlated non-normal geotechnical parameters in a more general way.It can serve as a general tool to construct the joint probability distribution of correlated geotechnical parameters based on incomplete data.The Gaussian copula using the Kendall method is superior to that using the Pearson method,which should be recommended for modelling and simulating the joint probability distribution of correlated geotechnical parameters.There exists a strong negative correlation between the two parameters underlying load-displacement curves.Neglecting such correlation will not capture the scatter in the measured load-displacement curves.These results substantially extend the application of the copula theory to multivariate simulation in geotechnical engineering.展开更多
Most failures or instabilities of geotechnical structures commonly result from shear failure in soil. In addition, many infrastructures are constructed within the unsaturated zone. Therefore, the determination of shea...Most failures or instabilities of geotechnical structures commonly result from shear failure in soil. In addition, many infrastructures are constructed within the unsaturated zone. Therefore, the determination of shear strength of unsaturated soil is crucial in geotechnical design. The soil-water characteristic curve(SWCC) is commonly used to estimate the shear strength of unsaturated soil because the direct measurement is time-consuming and costly. However, the uncertainty associated with the determined SWCC is rarely considered in the estimation of the shear strength. In this paper, the uncertainties of SWCC resulted from different factors are reviewed and discussed. The variability of the estimated shear strength for the unsaturated soil due to the uncertainty of SWCC associated with the best fit process is quantified by using the upper and lower bounds of the determined SWCC. On the other hand, the uncertainties of the estimated shear strength due to different initial void ratios or different confining pressures are quantified by adopting different SWCCs. As a result, it is recommended that the measured SWCC from the conventional Tempe cell or pressure plate needs to be corrected by considering different stress levels in the estimation of the shear strength of unsaturated soil.展开更多
基金supported by the National Basic Research Program of China ("973" Program) (Grant No. 2011CB013506)the National Natural Science Foundation of China (Grant Nos. 51028901 and 50839004)
文摘Determining the joint probability distribution of correlated non-normal geotechnical parameters based on incomplete statistical data is a challenging problem.This paper proposes a Gaussian copula-based method for modelling the joint probability distribution of bivariate uncertain data.First,the concepts of Pearson and Kendall correlation coefficients are presented,and the copula theory is briefly introduced.Thereafter,a Pearson method and a Kendall method are developed to determine the copula parameter underlying Gaussian copula.Second,these two methods are compared in computational efficiency,applicability,and capability of fitting data.Finally,four load-test datasets of load-displacement curves of piles are used to illustrate the proposed method.The results indicate that the proposed Gaussian copula-based method can not only characterize the correlation between geotechnical parameters,but also construct the joint probability distribution function of correlated non-normal geotechnical parameters in a more general way.It can serve as a general tool to construct the joint probability distribution of correlated geotechnical parameters based on incomplete data.The Gaussian copula using the Kendall method is superior to that using the Pearson method,which should be recommended for modelling and simulating the joint probability distribution of correlated geotechnical parameters.There exists a strong negative correlation between the two parameters underlying load-displacement curves.Neglecting such correlation will not capture the scatter in the measured load-displacement curves.These results substantially extend the application of the copula theory to multivariate simulation in geotechnical engineering.
基金Project supported by the National Natural Science Foundation of China(No.51878160)the National Key Research and Development Program of China(No.2017YFC00703408)the Research Funding from China Huaneng Group Co.Ltd.(No.HNKJ19-H17)。
文摘Most failures or instabilities of geotechnical structures commonly result from shear failure in soil. In addition, many infrastructures are constructed within the unsaturated zone. Therefore, the determination of shear strength of unsaturated soil is crucial in geotechnical design. The soil-water characteristic curve(SWCC) is commonly used to estimate the shear strength of unsaturated soil because the direct measurement is time-consuming and costly. However, the uncertainty associated with the determined SWCC is rarely considered in the estimation of the shear strength. In this paper, the uncertainties of SWCC resulted from different factors are reviewed and discussed. The variability of the estimated shear strength for the unsaturated soil due to the uncertainty of SWCC associated with the best fit process is quantified by using the upper and lower bounds of the determined SWCC. On the other hand, the uncertainties of the estimated shear strength due to different initial void ratios or different confining pressures are quantified by adopting different SWCCs. As a result, it is recommended that the measured SWCC from the conventional Tempe cell or pressure plate needs to be corrected by considering different stress levels in the estimation of the shear strength of unsaturated soil.
