Probabilistic stability analysis of an earth dam by Stochastic Finite Element Method based on field data

This paper performs a probabilistic stability analysis for an existing earthfill dam using a Stochastic Finite Element Method (SFEM) and considering the spatial variability of soil properties based on field data. Previous works on probabilistic slope stability analysis are generally based on hypothe...

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Bibliographic Details
Published in:Computers and geotechnics 2018-09, Vol.101, p.34-47
Main Authors: Mouyeaux, A., Carvajal, C., Bressolette, P., Peyras, L., Breul, P., Bacconnet, C.
Format: Article
Language:English
Subjects:
Case studies
Computer simulation
Dam stability
Dams
Data
Earth
Earth dams
Earthfill dam
Embankment dams
Embankment stability
Embankments
Finite element analysis
Finite element method
Geostatistics
Probabilistic analysis
Probability
Probability theory
Random variables
Reliability
Safety factors
Slope stability
Soil
Soil properties
Soil stability
Spatial variability
Spatial variations
Stability analysis
Statistical methods
Stochastic processes
Stochasticity
Strength reduction method
Variability
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Summary:This paper performs a probabilistic stability analysis for an existing earthfill dam using a Stochastic Finite Element Method (SFEM) and considering the spatial variability of soil properties based on field data. Previous works on probabilistic slope stability analysis are generally based on hypothetical data while using data from existing earth structures is not widespread. A probabilistic procedure based on field data is here implemented to analyze the stability of an existing embankment dam. The spatial variability of several soil properties is modeled from the geostatistical analysis of the available dataset of the dam studied. Random variables and random fields representing the variability of dam materials are integrated into an FE model by performing Monte Carlo simulations (MCS). This probabilistic analysis based on field data allowed to characterize the variability of the sliding safety factor for the case study of an existing dam.
ISSN:0266-352X
1873-7633
DOI:10.1016/j.compgeo.2018.04.017