New Advances in Cement and Concrete Research

Kim, Gun

doi:10.3390/ma16114162

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…Kim [49] highlighted the latest breakthroughs in cement and concrete research, including novel strategies for lowering carbon dioxide emissions in Portland cement production, such as the development of new building materials [50], and the development of mathematical modeling of the reliability of new composite materials [51]. Furthermore, it is necessary to highlight the importance of the prediction of the performance properties and reliability of new building materials [52].…”

Section: Methods To Estimate the Carbon Dioxide Removals Due To Carbo...mentioning

confidence: 99%

Carbon Dioxide Uptake by Brazilian Cement-Based Materials

da Silva Rego,

Sanjuán,

Mora

et al. 2023

Applied Sciences

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The worldwide cement industry plays an important role in addressing the climate change challenge. Brazil’s cement industry currently has 91 cement plants with an installed production capacity of 94 million tons per year and has started to calculate the net CO2 emissions to achieve a carbon-neutral cement sector by 2050. Accordingly, the carbon dioxide uptake due to mortar and concrete carbonation is subtracted from the carbon dioxide emitted by the chemical reaction for the calcination of lime, i.e., the calcination process performed during clinker production. Now-adays, the Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas (GHG) Inventories to report the GHG emissions do not include any calculation procedure to consider the mortar and concrete carbonation. However, the Intergovernmental Panel on Climate Change (IPCC)’s Sixth Assessment Report (AR6) recognizes the physico-chemical process known as carbonation. Brazilian net carbon dioxide emissions of cements produced from 1990 to 2019 are estimated considering the carbon dioxide uptake during the service-life and end-of-life and secondary usage stages (Tier 1). This is a fundamental scientific and technological novelty that changes the current approach to estimate the carbon dioxide emissions due to the Portland cement clinker production. Even considering the relative novelty of this approach, it should be promoted in the future and included in the national inventory report (NIR). The carbon dioxide uptake by mortar and concrete carbonation for 30 years is about 140 million tons. Within this thirty-year period about 483 million tons have been released due to the calcination process.

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Section: Methods To Estimate the Carbon Dioxide Removals Due To Carbo...mentioning

confidence: 99%

Carbon Dioxide Uptake by Brazilian Cement-Based Materials

da Silva Rego,

Sanjuán,

Mora

et al. 2023

Applied Sciences

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“…This process ensures reliability and accuracy in replicating concrete properties across different conditions. Overall, the ANN model enables efficient analysis and prediction of concrete properties, offering insights for sustainable construction practices and material optimization [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Prediction of Physical and Mechanical Properties of Concrete Containing Glass Aggregates

Maraqa,

Yasin,

Al-Sahawneh

et al. 2024

Civ Eng J

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This comprehensive study analyzes the use of crushed glass as both fine and coarse aggregate in concrete, as well as the prediction accuracy of Artificial Neural Networks (ANN). The primary objectives are to understand the interactions between concrete’s constituents and to assess the accuracy of ANN models in predicting concrete’s mechanical and physical properties. This is achieved using a two-decade experimental results dataset of concrete’s compressive and tensile strengths, slump, density, and the corresponding mix design proportions, including waste glass aggregate. A series of 70 concrete samples were carefully built and tested, with compressive strengths varying from 12 to 71 MPa and glass aggregate percentages ranging from 0-100%. These samples served as the basis for the creation of an input dataset and ANN targets. The ANN model underwent intensive training, validation, testing, and statistical regression analysis. The ANN models are exceptionally accurate, with a continuously low error margin of roughly 2%, highlighting their usefulness in matching experimental and predicted results. Validation techniques highlight the models' dependability, with consistently high coefficients of determination (R-values), including 0.99484, demonstrating their robustness in replicating complicated concrete properties. The data analysis shows a unique pattern, with optimum glass aggregate percentages in the range of 10–20%. Beyond this range, there is a noticeable decline in concrete properties. Finally, the study confirms the efficacy of ANN in predictive modeling while also validating the potential of crushed glass to replace natural aggregates in concrete. Doi: 10.28991/CEJ-2024-010-05-018 Full Text: PDF

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New Advances in Cement and Concrete Research

Abstract: The Special Issue (SI), “New Advances in Cement and Concrete Research”, highlights the latest breakthroughs in cement and concrete research [...]

Cited by 2 publications

References 11 publications

Carbon Dioxide Uptake by Brazilian Cement-Based Materials

Carbon Dioxide Uptake by Brazilian Cement-Based Materials

Artificial Neural Network-Based Prediction of Physical and Mechanical Properties of Concrete Containing Glass Aggregates

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