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Stability Analysis of an Embankment Supported by Spatially Variable Soil-Cement Columns
Soil-cement columns constructed by the deep mixing method (DMM) can effectively improve soft soil profiles for support of overlying structures. The soil-cement material can have highly variable strength properties resulting from a large number of factors. The difficulty in linking specific factors to soil-cement strength properties makes a reliability analysis using a Monte Carlo simulation approach appropriate. This paper investigates the effect of autocorrelation distance of strength properties on the overall stability of an embankment supported by soil-cement columns. Gaussian random fields of cohesion values are generated in MATLAB to be used in a FLAC finite difference model. Monte Carlo simulations are conducted to produce cumulative distributions of safety factor of the model for two autocorrelation distances. The resulting safety factors are compared and used to demonstrate a statistically significant difference in mean safety factors for different autocorrelation distances. The results suggest that the safety factor may decrease as autocorrelation distance reduces, indicating that deterministic analyses (i.e., as autocorrelation distance goes to ∞) may be unconservative for columns with high variability.
Stability Analysis of an Embankment Supported by Spatially Variable Soil-Cement Columns
Soil-cement columns constructed by the deep mixing method (DMM) can effectively improve soft soil profiles for support of overlying structures. The soil-cement material can have highly variable strength properties resulting from a large number of factors. The difficulty in linking specific factors to soil-cement strength properties makes a reliability analysis using a Monte Carlo simulation approach appropriate. This paper investigates the effect of autocorrelation distance of strength properties on the overall stability of an embankment supported by soil-cement columns. Gaussian random fields of cohesion values are generated in MATLAB to be used in a FLAC finite difference model. Monte Carlo simulations are conducted to produce cumulative distributions of safety factor of the model for two autocorrelation distances. The resulting safety factors are compared and used to demonstrate a statistically significant difference in mean safety factors for different autocorrelation distances. The results suggest that the safety factor may decrease as autocorrelation distance reduces, indicating that deterministic analyses (i.e., as autocorrelation distance goes to ∞) may be unconservative for columns with high variability.
Stability Analysis of an Embankment Supported by Spatially Variable Soil-Cement Columns
Coldwell, Eddie (Autor:in) / Khosravi, Mohammad (Autor:in) / Zaregarizi, Shahabeddin (Autor:in) / Perkins, Steven (Autor:in) / Montgomery, Jack (Autor:in)
Geo-Congress 2020 ; 2020 ; Minneapolis, Minnesota
Geo-Congress 2020 ; 507-515
21.02.2020
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Stability Analysis of an Embankment Supported by Spatially Variable Soil-Cement Columns
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