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Appl. Sci. 2017, 7(1), 35; doi:10.3390/app7010035

Strength Correlation and Prediction of Engineered Cementitious Composites with Microwave Properties

School of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China
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Author to whom correspondence should be addressed.
Academic Editors: Gangbing Song, Chuji Wang and Bo Wang
Received: 10 November 2016 / Revised: 7 December 2016 / Accepted: 14 December 2016 / Published: 27 December 2016
(This article belongs to the Special Issue Structural Health Monitoring (SHM) of Civil Structures)
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Abstract

This paper presents the results of microwave and mechanical measurements of engineered cementitious composites (ECCs) using a nondestructive microwave near-field detecting technique. The objective of this research is to investigate the correlations between effective conductance and compressive strength of ECCs at various curing ages under the influence of different initial water contents. Parallel measurements and regression analysis on compressive strength and microwave conductance were undertaken. It is shown that the strength evolution of ECCs can be accurately modeled and predicted by using microwave conductance at the early ages using bi-exponential functions. Compressive strength grows as a function of decreasing effective conductance, whereas the regression coefficients of the correlation models have a linear variation with water-to-binder ratios. These findings have highlighted the effectiveness of the microwave technique in detecting the variation of liquid phase morphology and pore structure. View Full-Text
Keywords: engineered cementitious composite; strength prediction; microwave technique; electrical conductance; structural health monitoring; water-to-binder ratio engineered cementitious composite; strength prediction; microwave technique; electrical conductance; structural health monitoring; water-to-binder ratio
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Chung, K.L.; Luo, J.; Yuan, L.; Zhang, C.; Qu, C. Strength Correlation and Prediction of Engineered Cementitious Composites with Microwave Properties. Appl. Sci. 2017, 7, 35.

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