Report of RILEM TC 281-CCC: insights into factors affecting the carbonation rate of concrete with SCMs revealed from data mining and machine learning approaches

Abstract The RILEM TC 281–CCC ‘‘Carbonation of concrete with supplementary cementitious materials’’ conducted a study on the effects of supplementary cementitious materials (SCMs) on the carbonation rate of blended cement concretes and mortars. In this context, a comprehensive database has been established, consisting of 1044 concrete and mortar mixes with their associated carbonation depth data over time. The dataset comprises mix designs with a large variety of binders with up to 94% SCMs, collected from the literature as well as unpublished testing reports. The data includes chemical composition and physical properties of the raw materials, mix-designs, compressive strengths, curing and carbonation testing conditions. Natural carbonation was recorded for several years in many cases with both indoor and outdoor results. The database has been analysed to investigate the effects of binder composition and mix design, curing and preconditioning, and relative humidity on the carbonation rate. Furthermore, the accuracy of accelerated carbonation testing as well as possible correlations between compressive strength and carbonation resistance were evaluated. One approach to summerise the physical and chemical resistance in one parameter is the ratio of water content to content of carbonatable CaO ( w /CaO reactive ratio). The analysis revealed that the w /CaO reactive ratio is a decisive factor for carbonation resistance, while curing and exposure conditions also influence carbonation. Under natural exposure conditions, the carbonation data exhibit significant variations. Nevertheless, probabilistic inference suggests that both accelerated and natural carbonation processes follow a square-root-of-time behavior, though accelerated and natural carbonation cannot be converted into each other without corrections. Additionally, a machine learning technique was employed to assess the influence of parameters governing the carbonation progress in concretes.

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Publication Details

Journal
Materials and Structures
Published
2024-10-23
DOI
https://doi.org/10.1617/s11527-024-02465-0
Citations
20
Primary Topic
Concrete and Cement Materials Research
Type
article
Field-Weighted Citation Impact
5.22

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article

Report of RILEM TC 281-CCC: insights into factors affecting the carbonation rate of concrete with SCMs revealed from data mining and machine learning approaches

Gregor J. G. Gluth, Yury Villagrán Zaccardi, Ikenna D. Uwanuakwa, Siham Kamali-Bernard et al.
20 citations
Materials and Structures
Concrete and Cement Materials Research
5.22
article

Report of RILEM TC 281-CCC: insights into factors affecting the carbonation rate of concrete with SCMs revealed from data mining and machine learning approaches

Gregor J. G. Gluth, Yury Villagrán Zaccardi, Ikenna D. Uwanuakwa, Siham Kamali-Bernard, Juan Manuel Etcheverry, Quoc Tri Phung, Sundar Rathnarajan, Hanne Vanoutrive, Charlotte Thiel, Bart Rogiers, Antonios Kanellopoulos, Isabel Milagre Martins, Zengfeng Zhao, Anya Vollpracht, Nele De Belie, Elke Gruyaert
article en
20 citations

Abstract

Abstract The RILEM TC 281–CCC ‘‘Carbonation of concrete with supplementary cementitious materials’’ conducted a study on the effects of supplementary cementitious materials (SCMs) on the carbonation rate of blended cement concretes and mortars. In this context, a comprehensive database has been established, consisting of 1044 concrete and mortar mixes with their associated carbonation depth data over time. The dataset comprises mix designs with a large variety of binders with up to 94% SCMs, collected from the literature as well as unpublished testing reports. The data includes chemical composition and physical properties of the raw materials, mix-designs, compressive strengths, curing and carbonation testing conditions. Natural carbonation was recorded for several years in many cases with both indoor and outdoor results. The database has been analysed to investigate the effects of binder composition and mix design, curing and preconditioning, and relative humidity on the carbonation rate. Furthermore, the accuracy of accelerated carbonation testing as well as possible correlations between compressive strength and carbonation resistance were evaluated. One approach to summerise the physical and chemical resistance in one parameter is the ratio of water content to content of carbonatable CaO ( w /CaO reactive ratio). The analysis revealed that the w /CaO reactive ratio is a decisive factor for carbonation resistance, while curing and exposure conditions also influence carbonation. Under natural exposure conditions, the carbonation data exhibit significant variations. Nevertheless, probabilistic inference suggests that both accelerated and natural carbonation processes follow a square-root-of-time behavior, though accelerated and natural carbonation cannot be converted into each other without corrections. Additionally, a machine learning technique was employed to assess the influence of parameters governing the carbonation progress in concretes.

Materials and StructuresVol. 57(9)
Tongji University (CN), OTH Regensburg (DE), Federal Institute For Materials Research and Testing (DE), University of Hertfordshire (GB), Indian Institute of Technology Madras (IN), Institut National des Sciences Appliquées de Rennes (FR), Ghent University (BE), Belgian Nuclear Research Centre (BE), Mersin Üniversitesi (TR), Université de Rennes (FR), National Laboratory for Civil Engineering (PT), Flemish Institute for Technological Research (BE), Near East University (CY), RWTH Aachen University (DE), KU Leuven (BE)
Universidad Nacional del Centro de la Provincia de Buenos Aires, Politecnico di Milano, RWTH Aachen University
Openalex Percentile: Top 4%
Concrete and Cement Materials Research
5.22
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