Integrating LEM with FEM through model correction factor method in reliability analysis of spatially variable slopes

Shui Hua Jiang, Iason Papaioannou, Chun Guang Li, Daniel Straub

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

Abstract

Reliability analysis of spatially variable slopes involves repeatedly evaluating the slope stability using a deterministic analysis method such as the limit equilibrium method (LEM) or the finite element method (FEM). The LEM is conceptually simple but requires assumptions on failure surfaces for slope stability analysis. The FEM tends to give a more realistic prediction of slope stability particularly when considering the spatial variability of soil properties, but has higher computational cost. The objective of this study is to combine the LEM and FEM to facilitate an efficient reliability assessment of spatially variable slopes. We adopt the model correction factor method (MCFM) to correct the reliability prediction obtained with the computationally efficient LEM. In the MCFM, an effectivity factor is introduced to push the idealized limit-state surface based on LEM to the more accurate limit-state surface based on FEM. We investigate the performance of the proposed approach in the reliability assessment of a c- slope example considering the spatial variability of the soil strength parameters.

Original languageEnglish
Pages947-953
Number of pages7
StatePublished - 2017
Event15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, IACMAG 2017 - Wuhan, China
Duration: 19 Oct 201723 Oct 2017

Conference

Conference15th International Conference of the International Association for Computer Methods and Advances in Geomechanics, IACMAG 2017
Country/TerritoryChina
CityWuhan
Period19/10/1723/10/17

Keywords

  • Effectivity Factor
  • Finite Element Method
  • Model Correction Factor Method
  • Slope Reliability
  • Spatial Variability

Fingerprint

Dive into the research topics of 'Integrating LEM with FEM through model correction factor method in reliability analysis of spatially variable slopes'. Together they form a unique fingerprint.

Cite this