Proceedings of the TMIC 2022 Slope Stability Conference (TMIC 2022)

Probabilistic Analysis of a Slope Using RLEM and Cross-Correlated Conditional Random Field

Authors
Sina Javankhoshdel1, *, Elahe Mohammadi2, Reza Jamshidi Chenari3, Terence Ma1, Brigid Cami1, Meghdad Payan3
1Rocscience, Toronto, Canada
2Shiraz University, Shiraz, Iran
3Guilan University, Guilan, Iran
*Corresponding author. Email: sina.javankhoshdel@rocscience.com
Corresponding Author
Sina Javankhoshdel
Available Online 1 March 2023.
DOI
10.2991/978-94-6463-104-3_8How to use a DOI?
Abstract

Probabilistic analyses of slopes using Random Limit Equilibrium Method (RLEM) have been extensively reported in literature. However, in these types of analyses, the generated random fields are based on assumed values of horizontal and vertical correlation lengths. In practice, horizontal and vertical correlation lengths can be measured using CPT data and the data can be used to condition the generated random fields. Conditioning random fields reduces the level of uncertainty in the analysis and helps the simulations to render more reasonable results. In this study, the stability analysis of a simple slope is used to investigate the influence of conditional and unconditional random fields. To generate spatially variable fields, first, some artificial borehole data are employed to correlate the spatially variable friction angle field. Then, considering some typical values for the variability of the cohesion random field and the possible cross-correlation between the two fields, a couple of scenarios are defined to synthesize the spatially variable realizations of the cohesion field. Then, the results of cross-correlated conditioned and unconditioned random fields are compared. The results show that conditioning random field and considering the cross-correlation between soil input parameters significantly reduce the probability of slope failure.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the TMIC 2022 Slope Stability Conference (TMIC 2022)
Series
Atlantis Highlights in Engineering
Publication Date
1 March 2023
ISBN
10.2991/978-94-6463-104-3_8
ISSN
2589-4943
DOI
10.2991/978-94-6463-104-3_8How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Sina Javankhoshdel
AU  - Elahe Mohammadi
AU  - Reza Jamshidi Chenari
AU  - Terence Ma
AU  - Brigid Cami
AU  - Meghdad Payan
PY  - 2023
DA  - 2023/03/01
TI  - Probabilistic Analysis of a Slope Using RLEM and Cross-Correlated Conditional Random Field
BT  - Proceedings of the TMIC 2022 Slope Stability Conference (TMIC 2022)
PB  - Atlantis Press
SP  - 71
EP  - 80
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-104-3_8
DO  - 10.2991/978-94-6463-104-3_8
ID  - Javankhoshdel2023
ER  -