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    Stochastic Method for Predicting Risk of Slope Failure Subjected to Unsaturated Infiltration Flow

    Source: International Journal of Geomechanics:;2017:;Volume ( 017 ):;issue: 008
    Author:
    Yuanyou Xia
    ,
    Mojtaba Mahmoodian
    ,
    Chun-Qing Li
    ,
    Annan Zhou
    DOI: 10.1061/(ASCE)GM.1943-5622.0000908
    Publisher: American Society of Civil Engineers
    Abstract: The increase of rainfall and rise of groundwater level can cause frequent failures of unsaturated soil slopes that result in catastrophic landslides. This paper proposes a stochastic method for predicting the risk of failure of an infinite soil slope subjected to unsaturated infiltration flow. Stochastic models for shear stress and strength at an arbitrary plane of an infinite slope are developed. The accuracy of the proposed method is verified with the Monte Carlo simulation method. The merit of the proposed method lies in its analytical form, which can easily facilitate practical applications. Furthermore, a risk-based sensitivity analysis is undertaken in this study to identify the factors that are the most random and that affect the slope failure most significantly. It is found in this study that the developed stochastic models can capture the randomness of all factors that contribute to slope failure. It is also found that the slope inclination angle (θ), soil air entry value (ψb), water table rise from matric suction (yb), dry soil unit weight (γd), and soil-specific constant (aϕ) are important random variables in the accurate prediction of slope failure. The paper concludes that the proposed stochastic method can serve as a tool for geotechnical engineers to predict the risk of slope failure with accuracy and ease.
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      Stochastic Method for Predicting Risk of Slope Failure Subjected to Unsaturated Infiltration Flow

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4239923
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    • International Journal of Geomechanics

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    contributor authorYuanyou Xia
    contributor authorMojtaba Mahmoodian
    contributor authorChun-Qing Li
    contributor authorAnnan Zhou
    date accessioned2017-12-16T09:12:23Z
    date available2017-12-16T09:12:23Z
    date issued2017
    identifier other%28ASCE%29GM.1943-5622.0000908.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4239923
    description abstractThe increase of rainfall and rise of groundwater level can cause frequent failures of unsaturated soil slopes that result in catastrophic landslides. This paper proposes a stochastic method for predicting the risk of failure of an infinite soil slope subjected to unsaturated infiltration flow. Stochastic models for shear stress and strength at an arbitrary plane of an infinite slope are developed. The accuracy of the proposed method is verified with the Monte Carlo simulation method. The merit of the proposed method lies in its analytical form, which can easily facilitate practical applications. Furthermore, a risk-based sensitivity analysis is undertaken in this study to identify the factors that are the most random and that affect the slope failure most significantly. It is found in this study that the developed stochastic models can capture the randomness of all factors that contribute to slope failure. It is also found that the slope inclination angle (θ), soil air entry value (ψb), water table rise from matric suction (yb), dry soil unit weight (γd), and soil-specific constant (aϕ) are important random variables in the accurate prediction of slope failure. The paper concludes that the proposed stochastic method can serve as a tool for geotechnical engineers to predict the risk of slope failure with accuracy and ease.
    publisherAmerican Society of Civil Engineers
    titleStochastic Method for Predicting Risk of Slope Failure Subjected to Unsaturated Infiltration Flow
    typeJournal Paper
    journal volume17
    journal issue8
    journal titleInternational Journal of Geomechanics
    identifier doi10.1061/(ASCE)GM.1943-5622.0000908
    treeInternational Journal of Geomechanics:;2017:;Volume ( 017 ):;issue: 008
    contenttypeFulltext
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