TY - JOUR A1 - Bernal, Susan A. A1 - Dhandapani, Yuvaraj A1 - Elakneswaran, Yogarajah A1 - Gluth, Gregor J. G. A1 - Gruyaert, Elke A1 - Juenger, Maria C. G. A1 - Lothenbach, Barbara A1 - Olonade, Kolawole Adisa A1 - Sakoparnig, Marlene A1 - Shi, Zhenguo A1 - Thiel, Charlotte A1 - van den Heede, Philip A1 - Vanoutrive, Hanne A1 - Von Greve-Dierfeld, Stefanie A1 - De Belie, Nele A1 - Provis, John L. T1 - Report of RILEM TC 281-CCC: A critical review of the standardised testing methods to determine carbonation resistance of concrete JF - Materials and Structures N2 - The chemical reaction between CO2 and a blended Portland cement concrete, referred to as carbonation, can lead to reduced performance, particularly when concrete is exposed to elevated levels of CO2 (i.e., accelerated carbonation conditions). When slight changes in concrete mix designs or testing conditions are adopted, conflicting carbonation results are often reported. The RILEM TC 281-CCC ‘Carbonation of Concrete with Supplementary Cementitious Materials’ has conducted a critical analysis of the standardised testing methodologies that are currently applied to determine carbonation resistance of concrete in different regions. There are at least 17 different standards or recommendations being actively used for this purpose, with significant differences in sample curing, pre-conditioning, carbonation exposure conditions, and methods used for determination of carbonation depth after exposure. These differences strongly influence the carbonation depths recorded and the carbonation coefficient values calculated. Considering the importance of accurately determining carbonation potential of concrete, not just for predicting their durability performance, but also for determining the amount of CO2 that concrete can re-absorb during or after its service life, it is imperative to recognise the applicability and limitations of the results obtained from different tests. This will enable researchers and practitioners to adopt the most appropriate testing methodologies to evaluate carbonation resistance, depending on the purpose of the conclusions derived from such testing (e. g. materials selection, service life prediction, CO2 capture potential). Y1 - 2024 U6 - https://doi.org/10.1617/s11527-024-02424-9 SN - 0025-5432 SN - 1359-5997 VL - 57 IS - 8 PB - Springer ER - TY - INPR A1 - Vollpracht, Anya A1 - Gluth, Gregor J. G. A1 - Rogiers, Bart A1 - Uwanuakwa, Ikenna D. A1 - Phung, Quoc Tri A1 - Zaccardi, Yury Villagran A1 - Thiel, Charlotte A1 - Vanoutrive, Hanne A1 - Etcheverry, Juan Manuel A1 - Gruyaert, Elke A1 - Kamali-Bernard, Siham A1 - Kanellopoulos, Antonios A1 - Zhao, Zengfeng A1 - Milagre Martins, Isabel A1 - Rathnarajan, Sundar A1 - De Belie, Nele T1 - 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 N2 - 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. The analysis revealed that the w/CaOreactive 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. KW - natural carbonation KW - accelerated carbonation KW - SCMs KW - database Y1 - 2024 U6 - https://doi.org/10.21203/rs.3.rs-4169492/v1 N1 - Verörffenticht bei Springer Nature: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/7776 PB - Research Square Platform LLC ER - TY - JOUR A1 - Vollpracht, A. A1 - Gluth, Gregor J. G. A1 - Rogiers, Bart A1 - Uwanuakwa, I. D. A1 - Phung, Quoc Tri A1 - Villagran Zaccardi, Y. A1 - Thiel, Charlotte A1 - Vanoutrive, H. A1 - Etcheverry, Juan Manuel A1 - Gruyaert, Elke A1 - Kamali-Bernard, Siham A1 - Kanellopoulos, Antonios A1 - Zhao, Zengfeng A1 - Milagre Martins, Isabel A1 - Rathnarajan, Sundar A1 - De Belie, Nele T1 - 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 JF - Materials and Structures N2 - 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/CaOreactive ratio). The analysis revealed that the w/CaOreactive 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. Y1 - 2024 U6 - https://doi.org/10.1617/s11527-024-02465-0 SN - 1359-5997 VL - 57 IS - 9 PB - Springer Science and Business Media ER -