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

Mojtahedi,S. F. F ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1007/s00366-018-0623-5
  3. Publisher: Springer London , 2018
  4. Abstract:
  5. 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 (Formula presented.), slope angle (Formula presented.) and cohesion (Formula presented.) 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. © 2018 Springer-Verlag London Ltd., part of Springer Nature
  6. Keywords:
  7. Factor of safety ; Monte Carlo simulation ; Regression analysis ; Sensitivity analysis ; Forecasting ; Intelligent systems ; Internal friction ; Monte Carlo methods ; Safety factor ; Angle of internal friction ; Effective parameters ; Geotechnical application ; MC simulation ; Probabilistic simulation ; Safety factor of slope ; Static conditions
  8. Source: Engineering with Computers ; 2018 , Pages 1-10 ; 01770667 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s00366-018-0623-5