Leveraging an integrated multivariate analytical approach towards strength enhancement of fly ash-based concrete
This work looks into the potential of fly ash additives, which is a by-product of coal combustion, to improve strengths in concrete. Very few of the existing studies consider the comprehensive multivariate approach of interactions between different types and proportions of fly ash additives in relat...
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Veröffentlicht in: | Multiscale and Multidisciplinary Modeling, Experiments and Design Experiments and Design, 2025, Vol.8 (1), Article 127 |
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Sprache: | eng |
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Zusammenfassung: | This work looks into the potential of fly ash additives, which is a by-product of coal combustion, to improve strengths in concrete. Very few of the existing studies consider the comprehensive multivariate approach of interactions between different types and proportions of fly ash additives in relation to various measures of concrete strength. Hence, this paper intends to surmount these limitations with the adoption of an integrated multivariate analytical methodology that involves Multivariate Analysis of Variance (MANOVA), multiple regression analysis, PCA, and correlation analysis using canonical correlation analysis. MANOVA is applied for the significance of fly ash additives with respect to multiple concrete strength dependent variables. Those significant predictors and their interactions drastically identified through the MANOVA are taken forward for analysis by Multiple Regression, followed by quantification for their effect on individual measures of strength. The dimensions will now be reduced using PCA to identify principal components that capture most of the variance. Finally, the relationships between sets of fly ash components and concrete strength measures are examined and quantified by CCA. The conjoined application of those methods has advantages in that MANOVA gives overall information on the effect of fly ash additives, Multiple Regression quantifies the contributions unique to each additive, PCA retains important information while simplifying the data, and CCA explains the complicated interrelations amongst variables for this process. The results indicate that specific fly ash additives, at optimal proportions, significantly enhance concrete strength, as revealed by high R-squared values in regression models that ensure a strong predictive power. This work contributes to valuable insight into the optimization of fly ash mixture variables for the development of more sustainable and robust concrete formulations, hence advancing the field of construction materials and environmental sustainability. |
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ISSN: | 2520-8160 2520-8179 |
DOI: | 10.1007/s41939-024-00721-y |