Stochastic back analysis of permeability coefficient using generalized Bayesian method

• Main Authors: Zheng Guilan, Wang Yuan, Wang Fei, Yang Jian
• Format: Article
• Language: English
• Published: Elsevier 2008-09-01
• Series: Water Science and Engineering
• Subjects: permeability coefficient; stochastic back analysis; generalized Bayesian method; variable metric algorithm
• Online Access: http://www.sciencedirect.com/science/article/pii/S1674237015300302

Owing to the fact that the conventional deterministic back analysis of the permeability coefficient cannot reflect the uncertainties of parameters, including the hydraulic head at the boundary, the permeability coefficient and measured hydraulic head, a stochastic back analysis taking consideration of uncertainties of parameters was performed using the generalized Bayesian method. Based on the stochastic finite element method (SFEM) for a seepage field, the variable metric algorithm and the generalized Bayesian method, formulas for stochastic back analysis of the permeability coefficient were derived. A case study of seepage analysis of a sluice foundation was performed to illustrate the proposed method. The results indicate that, with the generalized Bayesian method that considers the uncertainties of measured hydraulic head, the permeability coefficient and the hydraulic head at the boundary, both the mean and standard deviation of the permeability coefficient can be obtained and the standard deviation is less than that obtained by the conventional Bayesian method. Therefore, the present method is valid and applicable.