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Risk Assessment of Footings on Slopes in Spatially Variable Soils Considering Random Field Rotation
https://orcid.org/0000-0003-4772-0382
https://orcid.org/0000-0002-8371-2534
This paper presents the risk assessment of a footing-on-slope system that uses the random finite element method. The effect of a soil autocorrelation structure on the probability of failure and the associated risk is quantified. In this study, the anisotropic spatial variability of the soil is described with a major principal scale of fluctuation, a minor scale of fluctuation, and a rotation angle, and the spatial variability is modeled using the rotated random field. The generated random field is mapped onto a finite element model, which can quantify the bearing capacity of a footing on a slope. Further, the K-means cluster method is adopted to calculate the sliding area of the soil mass. Following Monte Carlo simulation, the probability of failure and the corresponding risk for footings on slopes are evaluated for various soil spatial variability scenarios. The results show the importance of considering the anisotropy of soils when attempting to identify the worst-case scenarios for risk.
Risk Assessment of Footings on Slopes in Spatially Variable Soils Considering Random Field Rotation
https://orcid.org/0000-0003-4772-0382
https://orcid.org/0000-0002-8371-2534
This paper presents the risk assessment of a footing-on-slope system that uses the random finite element method. The effect of a soil autocorrelation structure on the probability of failure and the associated risk is quantified. In this study, the anisotropic spatial variability of the soil is described with a major principal scale of fluctuation, a minor scale of fluctuation, and a rotation angle, and the spatial variability is modeled using the rotated random field. The generated random field is mapped onto a finite element model, which can quantify the bearing capacity of a footing on a slope. Further, the K-means cluster method is adopted to calculate the sliding area of the soil mass. Following Monte Carlo simulation, the probability of failure and the corresponding risk for footings on slopes are evaluated for various soil spatial variability scenarios. The results show the importance of considering the anisotropy of soils when attempting to identify the worst-case scenarios for risk.
Risk Assessment of Footings on Slopes in Spatially Variable Soils Considering Random Field Rotation
https://orcid.org/0000-0003-4772-0382
https://orcid.org/0000-0002-8371-2534
This paper presents the risk assessment of a footing-on-slope system that uses the random finite element method. The effect of a soil autocorrelation structure on the probability of failure and the associated risk is quantified. In this study, the anisotropic spatial variability of the soil is described with a major principal scale of fluctuation, a minor scale of fluctuation, and a rotation angle, and the spatial variability is modeled using the rotated random field. The generated random field is mapped onto a finite element model, which can quantify the bearing capacity of a footing on a slope. Further, the K-means cluster method is adopted to calculate the sliding area of the soil mass. Following Monte Carlo simulation, the probability of failure and the corresponding risk for footings on slopes are evaluated for various soil spatial variability scenarios. The results show the importance of considering the anisotropy of soils when attempting to identify the worst-case scenarios for risk.
Risk Assessment of Footings on Slopes in Spatially Variable Soils Considering Random Field Rotation
ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng.
2022-09-01
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2017