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Probabilistic investigation of RFEM topologies for slope stability analysis


Dyson, AP and Tolooiyan, A, Probabilistic investigation of RFEM topologies for slope stability analysis, Computers and Geotechnics, 114 Article 103129. ISSN 0266-352X (2019) [Refereed Article]

Copyright Statement

Copyright 2019 Elsevier Ltd.

DOI: doi:10.1016/j.compgeo.2019.103129


The Random Finite Element Method (RFEM) is an increasingly popular tool in geotechnical engineering, especially for analysis of spatial variation and uncertainty in slope stability. Although the method has gained prominence in recent years, topological effects of strong and weak zones and the impact of their locations remain largely unknown. Although numerous potential slip surface realisations can be generated with RFEM, probabilistic failure statistics are often governed by several representative slip surfaces (RSS). In this research, random field similarity methods and clustering techniques are coupled with RFEM slope stability simulation to determine the impact of shear strength spatial patterns on slope failure mechanisms and safety factors. Regions of significance are highlighted within a case study of a Victorian open-cutbrown coal mine, with particular attention given to the effects on the slope failure surface as well the factor of safety. Results are presented of Factor of Safety distributions when particular slip surfaces and clustering constraints are imposed, providing further understanding of the impacts of shear strength characteristics on probabilistic simulation results.

Item Details

Item Type:Refereed Article
Keywords:Random field, slope stability, random finite element method, RFEM, probabilistic methods, failure surface, topology
Research Division:Engineering
Research Group:Civil engineering
Research Field:Civil geotechnical engineering
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Dyson, AP (Dr Ashley Dyson)
UTAS Author:Tolooiyan, A (Dr Ali Tolooiyan)
ID Code:135234
Year Published:2019
Web of Science® Times Cited:10
Deposited By:Engineering
Deposited On:2019-10-08
Last Modified:2021-01-28

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