Prediction of Effective Chloride Diffusivity of Cement Paste and Mortar from Microstructural Features
Publication: Journal of Materials in Civil Engineering
Volume 32, Issue 8
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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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Porosity data of all samples at all ages.
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Electrical resistivity data of all samples at all ages.
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Nonsteady state migration diffusivity data of all samples at all ages.
Acknowledgments
The financial support from the Zhejiang Provincial Natural Science Foundation of China (Grant No. LZ20E080003), the Ministry of Science and Technology of the People’s Republic of China (973 Program) (Grant No. 2015CB655103), and the National Natural Science Foundation of China (Grant Nos. 51978620 and 51678529) are gratefully acknowledged.
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Published In
Journal of Materials in Civil Engineering
Volume 32 • Issue 8 • August 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Oct 13, 2019
Accepted: Jan 27, 2020
Published online: May 27, 2020
Published in print: Aug 1, 2020
Discussion open until: Oct 27, 2020
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