Yes / The instability of soil slopes is directly related to both the shear parameters of the soil material and the groundwater, which usually causes some uncertainty. In this study, a novel method, the element failure probability method (EFP), is proposed to analyse the failure of soil slopes. Based on the upper bound theory, finite element discretization, and the stochastic programming theory, an upper bound stochastic programming model is established by simultaneously considering the randomness of shear parameters and groundwater level to analyse the reliability of slopes. The model is then solved by using the Monte-Carlo method based on the random shear parameters and groundwater levels. Finally, a formula is derived for the element failure probability (EFP) based on the safety factors and velocity fields of the upper bound method. The probability of a slope failure can be calculated by using the safety factor, and the distribution of failure regions in space can be determined by using the location information of the element. The proposed method is validated by using a classic example. This study has theoretical value for further research attempting to advance the application of plastic limit analysis to analyse slope reliability. / National Natural Science Foundation of China (grant no. 51564026), the Research Foundation of Kunming University of Science and Technology (grant no. KKSY201904006) and the Key Laboratory of Rock Mechanics and Geohazards of Zhejiang Province (grant no. ZJRM-2018-Z-02).
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/18421 |
| Date | 28 April 2021 |
| Creators | Li, Z., Chen, Y., Guo, Yakun, Zhang, X., Du, S. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Accepted manuscript |
| Rights | © 2021 American Society of Civil Engineers. This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://doi.org/10.1061/(ASCE)GM.1943-5622.0002063, Unspecified |
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