Inhomogeneities of carbonation depth distributions in recycled aggregate concretes: A visualisation and quantification study

Renjie Mi; Ganghua Pan

doi:10.1016/j.conbuildmat.2022.127300

Inhomogeneities of carbonation depth distributions in recycled aggregate concretes : A visualisation and quantification study

Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review

Overview

1 Scopus Citations

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Author(s)

Renjie Mi
Ganghua Pan

Related Research Unit(s)

Department of Architecture and Civil Engineering

Detail(s)

Original language	English
Article number	127300
Journal / Publication	Construction and Building Materials
Volume	330
Online published	30 Mar 2022
Publication status	Published - 2 May 2022

Link(s)

DOI	DOI https://doi.org/10.1016/j.conbuildmat.2022.127300 Final Published version
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Link to Scopus	https://www.scopus.com/record/display.uri?eid=2-s2.0-85127168417&origin=recordpage
Permanent Link	https://scholars.cityu.edu.hk/en/publications/publication(625e02bd-da78-479c-b963-2587497b54ff).html

Abstract

The carbonation depths nonuniformly distribute in recycled aggregate concrete (RAC) because it has two kinds of mortars and three kinds of interfacial transition zones; but the inhomogeneity of the distribution is underestimated. Hereby, the inhomogeneities in RACs prepared with modelled industrially-produced and laboratory-produced recycled coarse aggregates (RCAs) were visualised and quantified using a proposed method. Afterwards, the influences of RCA types, RCA replacement ratios and strengthening methods of RCA on the average carbonation depths, their errors and the maximum carbonation depths were examined. The results showed that the carbonation depth distributions of RACs presented clear inhomogeneities. Utilising the CO₂ curing technology for RCA might not reduce the inhomogeneities; but light effects can be observed through selecting a proper RCA or using a nano-SiO₂ slurry soaking method for RCA. Reducing the maximum carbonation depth of RAC by selecting an appropriate RCA was more effective compared with by using the nano-SiO₂ slurry soaking method. Besides, predicting the carbonation degree of RAC by using the maximum carbonation depth was more conservative than by using the average carbonation depth.