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    Prediction of Effective Chloride Diffusivity of Cement Paste and Mortar from Microstructural Features

    Source: Journal of Materials in Civil Engineering:;2020:;Volume ( 032 ):;issue: 008
    Author:
    Rui He
    ,
    Chuanqing Fu
    ,
    Hongyan Ma
    ,
    Hailong Ye
    ,
    Xianyu Jin
    DOI: 10.1061/(ASCE)MT.1943-5533.0003288
    Publisher: ASCE
    Abstract: In this paper, a two-step model is proposed to predict the effective chloride diffusivity of cement paste and cement mortar. The prediction effective chloride diffusivity results of cement paste and cement mortar are compared with two different experimental method results. In the two-step model, the effective chloride diffusivity of cement paste is predicted based on the porosity and the effective diffusivity of the solid phase using the general effective media (GEM) model. Based on the GEM model, the effective chloride diffusivity of cement mortar is predicted by the composite spheres assemblage (CSA) model, which considers the aggregate volume fraction and the effective diffusivity of the interfacial transition zone (ITZ). As important inputs of the model, the porosities of cement paste and mortar are obtained by low field nuclear magnetic resonance (LF-NMR). The effective chloride diffusivities of cement paste and mortar are also determined by a newly proposed modified noncontact electrical resistivity measurement (MN-CM) based on the Nernst-Einstein equation and the rapid chloride migration test (RCMT). The results show that the effective chloride diffusivities from the proposed prediction model is in good agreement with the experimental results. The proposed prediction model could be used to predict the diffusivity of cement-based materials.
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      Prediction of Effective Chloride Diffusivity of Cement Paste and Mortar from Microstructural Features

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4267219
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    contributor authorRui He
    contributor authorChuanqing Fu
    contributor authorHongyan Ma
    contributor authorHailong Ye
    contributor authorXianyu Jin
    date accessioned2022-01-30T20:50:34Z
    date available2022-01-30T20:50:34Z
    date issued8/1/2020 12:00:00 AM
    identifier other%28ASCE%29MT.1943-5533.0003288.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4267219
    description abstractIn this paper, a two-step model is proposed to predict the effective chloride diffusivity of cement paste and cement mortar. The prediction effective chloride diffusivity results of cement paste and cement mortar are compared with two different experimental method results. In the two-step model, the effective chloride diffusivity of cement paste is predicted based on the porosity and the effective diffusivity of the solid phase using the general effective media (GEM) model. Based on the GEM model, the effective chloride diffusivity of cement mortar is predicted by the composite spheres assemblage (CSA) model, which considers the aggregate volume fraction and the effective diffusivity of the interfacial transition zone (ITZ). As important inputs of the model, the porosities of cement paste and mortar are obtained by low field nuclear magnetic resonance (LF-NMR). The effective chloride diffusivities of cement paste and mortar are also determined by a newly proposed modified noncontact electrical resistivity measurement (MN-CM) based on the Nernst-Einstein equation and the rapid chloride migration test (RCMT). The results show that the effective chloride diffusivities from the proposed prediction model is in good agreement with the experimental results. The proposed prediction model could be used to predict the diffusivity of cement-based materials.
    publisherASCE
    titlePrediction of Effective Chloride Diffusivity of Cement Paste and Mortar from Microstructural Features
    typeJournal Paper
    journal volume32
    journal issue8
    journal titleJournal of Materials in Civil Engineering
    identifier doi10.1061/(ASCE)MT.1943-5533.0003288
    page10
    treeJournal of Materials in Civil Engineering:;2020:;Volume ( 032 ):;issue: 008
    contenttypeFulltext
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