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Erschienen in: Engineering with Computers 2/2019

01.06.2018 | Original Article

A novel probabilistic simulation approach for forecasting the safety factor of slopes: a case study

verfasst von: S. Farid F. Mojtahedi, Sanaz Tabatabaee, Mahyar Ghoroqi, Mehran Soltani Tehrani, Behrouz Gordan, Milad Ghoroqi

Erschienen in: Engineering with Computers | Ausgabe 2/2019

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Abstract

Stabilization of slopes is considered as the aim of the several geotechnical applications such as embankment, tunnel, highway, building and railway and dam. Therefore, evaluation and precise prediction of the factor of safety (FoS) of slopes can be useful in designing these important structures. This research is carried out to evaluate the ability of Monte Carlo (MC) technique for the forecasting the FoS of many homogenous slopes in the static condition. Moreover, the sensitivity of the FoS on the effective parameters was identified. To do this, the most important factors on FoS, such as angle of internal friction \((\emptyset )\), slope angle \((\alpha )\) and cohesion \((C)\) were investigated and used as the inputs to forecast the FoS. Then, a regression analysis was performed, and the results were used for the FoS prediction using MC. The obtained results of MC simulation were very close with the actual FoS values. The mean of the simulated FoS by MC was achieved as 1.32, while, according to actual FoSs, it was 1.27. These results showed that MC is an acceptable technique to estimate the FoS of slopes with high level of accuracy. Moreover, based on the results of correlation and regression sensitivity analyses, it was concluded that angle of internal friction, was the most influential one on the results of FoS in both types of sensitivity analyses.

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Metadaten
Titel
A novel probabilistic simulation approach for forecasting the safety factor of slopes: a case study
verfasst von
S. Farid F. Mojtahedi
Sanaz Tabatabaee
Mahyar Ghoroqi
Mehran Soltani Tehrani
Behrouz Gordan
Milad Ghoroqi
Publikationsdatum
01.06.2018
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 2/2019
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-018-0623-5

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