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Comparative approaches to probabilistic finite element methods for slope stability analysis


Dyson, AP and Tolooiyan, A, Comparative approaches to probabilistic finite element methods for slope stability analysis, Simulation Modelling Practice and Theory, 100 Article 102061. ISSN 1569-190X (2019) [Refereed Article]

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Copyright 2020 Elsevier Science B.V

DOI: doi:10.1016/j.simpat.2019.102061


Probabilistic slope stability analyses are often preferable to deterministic methods when soils are inherently heterogeneous, or the reliability of geotechnical parameters is largely unknown. These methods are suitable for evaluating the risk of slope failure by producing a range of potential scenarios for the slope stability factor of safety. Several probabilistic methods including the Point Estimate Method, Monte Carlo Method and Random Finite Element Method, can be combined with the Finite Element technique. In this study, various shear strength distributions are considered for three different probabilistic Finite Element Methods to determine Factor of Safety and Probability of Failure distributions, based on the associated method of slope stability analysis. Results are presented for a case study of an Australian open-cut coal mine, with a range of shear strength parameter distributions for coal and interseam cohesive materials considered. Coal and interseam shear strength parameters are varied independently, to determine the effects of each material on the slope Factor of Safety.

Item Details

Item Type:Refereed Article
Keywords:Random Finite Element Method, Monte Carlo simulation, point estimate method, spatial variation, slope stability analysis
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:140444
Year Published:2019
Web of Science® Times Cited:14
Deposited By:Engineering
Deposited On:2020-08-18
Last Modified:2022-08-30

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