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Strength and Acid Resistance of Ceramic-Based Self-Compacting Alkali-Activated Concrete: Optimizing and Predicting Assessment
The development of self-compacting alkali-activated concrete (SCAAC) has become a hot topic in the scientific community; however, most of the existing literature focuses on the utilization of fly ash (FA), ground blast furnace slag (GBFS), silica fume (SF), and rice husk ash (RHA) as the binder. In...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8540594/ https://www.ncbi.nlm.nih.gov/pubmed/34683800 http://dx.doi.org/10.3390/ma14206208 |
Sumario: | The development of self-compacting alkali-activated concrete (SCAAC) has become a hot topic in the scientific community; however, most of the existing literature focuses on the utilization of fly ash (FA), ground blast furnace slag (GBFS), silica fume (SF), and rice husk ash (RHA) as the binder. In this study, both the experimental and theoretical assessments using response surface methodology (RSM) were taken into account to optimize and predict the optimal content of ceramic waste powder (CWP) in GBFS-based self-compacting alkali-activated concrete, thus promoting the utilization of ceramic waste in construction engineering. Based on the suggested design array from the RSM model, experimental tests were first carried out to determine the optimum CWP content to achieve reasonable compressive, tensile, and flexural strengths in the SCAAC when exposed to ambient conditions, as well as to minimize its strength loss, weight loss, and UPVL upon exposure to acid attack. Based on the results, the optimum content of CWP that satisfied both the strength and durability aspects was 31%. In particular, a reasonable reduction in the compressive strength of 16% was recorded compared to that of the control specimen (without ceramic). Meanwhile, the compressive strength loss of SCAAC when exposed to acid attack minimized to 59.17%, which was lower than that of the control specimen (74.2%). Furthermore, the developed RSM models were found to be reliable and accurate, with minimum errors (RMSE < 1.337). In addition, a strong correlation (R > 0.99, R(2) < 0.99, adj. R(2) < 0.98) was observed between the predicted and actual data. Moreover, the significance of the models was also proven via ANOVA, in which p-values of less than 0.001 and high F-values were recorded for all equations. |
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