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    Estimation of Resilient Modulus of Unbound Aggregates Using Performance-Related Base Course Properties

    Source: Journal of Materials in Civil Engineering:;2015:;Volume ( 027 ):;issue: 006
    Author:
    Fan Gu
    ,
    Hakan Sahin
    ,
    Xue Luo
    ,
    Rong Luo
    ,
    Robert L. Lytton
    DOI: 10.1061/(ASCE)MT.1943-5533.0001147
    Publisher: American Society of Civil Engineers
    Abstract: This study aims at developing an accurate and efficient methodology to estimate the resilient modulus of unbound aggregates. First, a new resilient modulus model is proposed to incorporate the moisture dependence of the resilient modulus in addition to the stress dependence in existing models. Second, prediction models are developed to conveniently and accurately determine the coefficients in the proposed model. In order to characterize the moisture dependence of unbound aggregates, the degree of saturation and the matric suction parameter are added into the proposed model. The soil-water characteristic curve (SWCC) is used to determine the matric suction value at any given moisture content. The moisture dependence of the model is validated for selected materials with different moisture contents. In order to develop prediction models for the coefficients in the proposed model, laboratory experiments and multiple regression analysis are conducted on 20 different base course materials. The laboratory experiments include the improved repeated load triaxial test and tests to measure performance-related base course properties. A new test protocol is developed for the improved repeated load triaxial test, which is better adapted to the stress state of the base course under the actual traffic load than the current test protocols. A series of repeatable and performance-related base course properties are measured and used to develop the prediction models based on multiple regression analysis. These newly proposed properties include methylene blue value (MBV), percent fines content (pfc), gradation of particle sizes, and shape, angularity, and texture of aggregates. The developed prediction models have higher
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      Estimation of Resilient Modulus of Unbound Aggregates Using Performance-Related Base Course Properties

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    http://yetl.yabesh.ir/yetl1/handle/yetl/79612
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    contributor authorFan Gu
    contributor authorHakan Sahin
    contributor authorXue Luo
    contributor authorRong Luo
    contributor authorRobert L. Lytton
    date accessioned2017-05-08T22:23:51Z
    date available2017-05-08T22:23:51Z
    date copyrightJune 2015
    date issued2015
    identifier other44024016.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/79612
    description abstractThis study aims at developing an accurate and efficient methodology to estimate the resilient modulus of unbound aggregates. First, a new resilient modulus model is proposed to incorporate the moisture dependence of the resilient modulus in addition to the stress dependence in existing models. Second, prediction models are developed to conveniently and accurately determine the coefficients in the proposed model. In order to characterize the moisture dependence of unbound aggregates, the degree of saturation and the matric suction parameter are added into the proposed model. The soil-water characteristic curve (SWCC) is used to determine the matric suction value at any given moisture content. The moisture dependence of the model is validated for selected materials with different moisture contents. In order to develop prediction models for the coefficients in the proposed model, laboratory experiments and multiple regression analysis are conducted on 20 different base course materials. The laboratory experiments include the improved repeated load triaxial test and tests to measure performance-related base course properties. A new test protocol is developed for the improved repeated load triaxial test, which is better adapted to the stress state of the base course under the actual traffic load than the current test protocols. A series of repeatable and performance-related base course properties are measured and used to develop the prediction models based on multiple regression analysis. These newly proposed properties include methylene blue value (MBV), percent fines content (pfc), gradation of particle sizes, and shape, angularity, and texture of aggregates. The developed prediction models have higher
    publisherAmerican Society of Civil Engineers
    titleEstimation of Resilient Modulus of Unbound Aggregates Using Performance-Related Base Course Properties
    typeJournal Paper
    journal volume27
    journal issue6
    journal titleJournal of Materials in Civil Engineering
    identifier doi10.1061/(ASCE)MT.1943-5533.0001147
    treeJournal of Materials in Civil Engineering:;2015:;Volume ( 027 ):;issue: 006
    contenttypeFulltext
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