Water Science and Engineering 2008, 1(3) 83-92  DOI:   10.3882/j.issn.1674-2370.2008.03.009   ISSN: 1674-2370 CN: 32-1785/TV

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Keywords
permeability coefficient
stochastic back analysis
generalized Bayesian method
variable metric algorithm
Authors
Gui-lan ZHENG
Yuan WANG
Fei WANG
Jian YANG
PubMed
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Stochastic back analysis of permeability coefficient using generalized Bayesian method

Gui-lan ZHENG1, Yuan WANG*2, 3, Fei WANG2, 3, Jian YANG2, 3

1. College of Traffic, College of Ocean, Hohai University, Nanjing 210098, P. R. China
2. Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering, Hohai University, Nanjing 210098, P. R. China
3. Geotechnical Research Institute of Hohai University, Nanjing 210098, P. R. China

Abstract

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.

Keywords permeability coefficient   stochastic back analysis   generalized Bayesian method   variable metric algorithm  
Received 2008-07-17 Revised 2008-09-07 Online:  
DOI: 10.3882/j.issn.1674-2370.2008.03.009
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Corresponding Authors: Yuan WANG
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