Modelos predictivos e impacto ambiental de la carbonatación del hormigón con agregado reciclado: Una revisión

  • Pico-Cortés C
  • Villagrán-Zaccardi Y
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Abstract

This article reviewes the prediction of carbonation in concrete with recycled aggregate in all stages and aspects related to sustainability. Concrete carbonation has two sides. In reinforced concrete, the research approach aims to prevent the advance of the carbonation depth so that the pH drop does not lead to reinforcement corrosion. The parameter of this approach is the carbonation coefficient. In non-reinforced concrete, priority is given to the higher absorption and sequestration of carbon dioxide to reduce global warming. Thus, obtaining the parameter degree of carbonation is necessary. In the case of recycled concrete, these two parameters become more critical due to its particular pore structure. The correlation between natural or accelerated carbonation and other durability properties is also described. Different predictive carbonation models are mentioned, including those based on artificial intelligence, and the service life calculation is introduced. The literature review shows a growing trend in measuring transport properties to use them within predictive modeling. This modeling is based on the fact that these predictions have higher reliability than those derived from mechanical or fresh-state properties. As for performance verification, it is required to compare model results with experimental carbonation results under realistic environmental conditions. Checking a possible dependence with experimentally determined recycled aggregate characteristics is also recommended. Finally, some considerations and actions are proposed to analyze the sustainable aspects of the material life cycle effectively.

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APA

Pico-Cortés, C., & Villagrán-Zaccardi, Y. (2024). Modelos predictivos e impacto ambiental de la carbonatación del hormigón con agregado reciclado: Una revisión. Ingeniare. Revista Chilena de Ingeniería, 31. https://doi.org/10.4067/s0718-33052023000100237

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