Design and sensitivity analysis of rock slope using Monte Carlo simulation
|Author:||Aladejare, Adeyemi Emman1; Akeju, Victor Oluwatosin2|
1Oulu Mining School, University of Oulu, Pentti Kaiteran katu 1, 90014, Oulu, Finland
2Department of Mining Engineering, Federal University of Technology, Akure, Nigeria
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020040610402
|Publish Date:|| 2020-04-06
A probabilistic approach that is based on Monte Carlo simulation (MCS) was developed in this study to design and perform sensitivity analysis of rock slope. The probabilistic approach uses MCS to perform a series of single objective optimizations for design of rock slope and to perform sensitivity analysis of rock slope stability. The MCS-based approach was used to evaluate the failure probability of a rock slope system and to determine a safe maximum slope height for rock slope design. To achieve this, the performance of different rock properties and rock slope conditions were explicitly considered towards achieving the target reliability index of the rock slope. The approach can achieve multiple rock slope design specifications using different target reliability indexes from a single run of MCS. The proposed probabilistic approach was illustrated through an example of rock slope design to determine feasible designs under different rock slope conditions. Also, sensitivity studies were performed to explore the effects of uncertainties in tension crack depth and water depth in tension crack, and variability in rock unit weight. The results show that the effects of uncertainties and variability on rock slope stability can be significant and should be incorporated during design analysis. Incorporating such uncertainties and variability in rock slope design is achieved with relative ease using the proposed approach.
Geotechnical and geological engineering
|Pages:||573 - 585|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
Open access funding provided by University of Oulu including Oulu University Hospital.
© The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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.