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    Simplified Model to Predict Features of Soil–Water Retention Curve Accounting for Stress State Conditions

    Source: International Journal of Geomechanics:;2020:;Volume ( 020 ):;issue: 003
    Author:
    Suman Roy
    ,
    Sathiyamoorthy Rajesh
    DOI: 10.1061/(ASCE)GM.1943-5622.0001591
    Publisher: ASCE
    Abstract: Stress state is a significant factor influencing the features of the soil–water retention curve (SWRC) under realistic in-situ conditions. The SWRC under different stress state conditions can be evaluated through experimental procedures and various constitutive models. Often, these models require experimental SWRC observations for at least two stress state conditions (i.e., a minimum of two reference SWRCs) to calibrate model parameters, which is difficult owing to the high time consumption associated with such experiments. In the present study, a simplified model is proposed by considering experimental SWRC observations for the single stress state condition to predict SWRC features for other stress state conditions in the gravimetric plane. An attempt has been made to extend the proposed model in the degree of the saturation plane using certain void ratio constitutive relations. The proposed model was validated against several SWRC experimental data sets available in the literature. Good agreement was found between the predicted and measured experimental results in the literature, with wide variations in the type of soils, stress conditions, and sample preparation methodologies. The proposed model is also capable of capturing the variation in key SWRC parameters considering the way the quantity of water is defined. The proposed method is quite simple and hence can be widely used for engineering applications.
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      Simplified Model to Predict Features of Soil–Water Retention Curve Accounting for Stress State Conditions

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4265628
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    • International Journal of Geomechanics

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    contributor authorSuman Roy
    contributor authorSathiyamoorthy Rajesh
    date accessioned2022-01-30T19:36:20Z
    date available2022-01-30T19:36:20Z
    date issued2020
    identifier other%28ASCE%29GM.1943-5622.0001591.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4265628
    description abstractStress state is a significant factor influencing the features of the soil–water retention curve (SWRC) under realistic in-situ conditions. The SWRC under different stress state conditions can be evaluated through experimental procedures and various constitutive models. Often, these models require experimental SWRC observations for at least two stress state conditions (i.e., a minimum of two reference SWRCs) to calibrate model parameters, which is difficult owing to the high time consumption associated with such experiments. In the present study, a simplified model is proposed by considering experimental SWRC observations for the single stress state condition to predict SWRC features for other stress state conditions in the gravimetric plane. An attempt has been made to extend the proposed model in the degree of the saturation plane using certain void ratio constitutive relations. The proposed model was validated against several SWRC experimental data sets available in the literature. Good agreement was found between the predicted and measured experimental results in the literature, with wide variations in the type of soils, stress conditions, and sample preparation methodologies. The proposed model is also capable of capturing the variation in key SWRC parameters considering the way the quantity of water is defined. The proposed method is quite simple and hence can be widely used for engineering applications.
    publisherASCE
    titleSimplified Model to Predict Features of Soil–Water Retention Curve Accounting for Stress State Conditions
    typeJournal Paper
    journal volume20
    journal issue3
    journal titleInternational Journal of Geomechanics
    identifier doi10.1061/(ASCE)GM.1943-5622.0001591
    page04019191
    treeInternational Journal of Geomechanics:;2020:;Volume ( 020 ):;issue: 003
    contenttypeFulltext
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