University of Oulu

Ali Akbar Hekmatzadeh, Farshad Zarei, Ali Johari, Ali Torabi Haghighi, Reliability analysis of stability against piping and sliding in diversion dams, considering four cutoff wall configurations, Computers and Geotechnics, Volume 98, 2018, Pages 217-231, ISSN 0266-352X,

Reliability analysis of stability against piping and sliding in diversion dams, considering four cutoff wall configurations

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Author: Hekmatzadeh, Ali Akbar1; Zarei, Farshad1; Johari, Ali1;
Organizations: 1Department of Civil and Environmental Engineering, Shiraz University of Technology, Po. Box 71555-313, Shiraz, Iran
2Water Resources and Environmental Engineering Research Group, University of Oulu, PO Box 4300, FIN-90014, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
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Language: English
Published: Elsevier, 2018
Publish Date: 2020-02-27


The stability against piping and sliding, which is subject to numerous sources of uncertainty, is of great importance in the design of diversion dams. In this study, the performance of four cutoff wall configurations, including a single wall and two walls with half the length of the single wall, was evaluated stochastically using the random finite element method. The Cholesky decomposition technique in conjunction with three types of Auto-Correlation Function (ACF) was employed to generate numerous random fields. The results indicate that the probabilities of failure related to different cutoff wall configurations are similar, considering isotropic hydraulic conductivity. However, there are noticeable differences between the probabilities of failure of these configurations in anisotropic situations. Moreover, the use of a single cutoff wall on the upstream face of an impervious blanket provides the lowest probability of failure for piping. In addition, the exponential ACF ends up with greater exit hydraulic gradients than the second-order Markov and binary noise ACFs. In addition, the sliding stability of the ordinary and earthquake load combinations was examined stochastically using random field theory and Monte Carlo Simulation (MCS). The probability of failure appears to increase with an increase in the autocorrelation distance.

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Series: Computers and geotechnics
ISSN: 0266-352X
ISSN-E: 1873-7633
ISSN-L: 0266-352X
Volume: 98
Pages: 217 - 231
DOI: 10.1016/j.compgeo.2018.02.019
Type of Publication: A1 Journal article – refereed
Field of Science: 1171 Geosciences
Copyright information: © 2018 The Authors. Published by Elsevier Inc. This manuscript version is made available under the CC-BY-NC-ND 4.0 license