ArticleMaterials (Basel, Switzerland)2021
Principal Component Analysis as a Statistical Tool for Concrete Mix Design.
Article in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Functional Variability and Interchangeability of Commercial Limestone Powders in Concrete: An Experimental and Multivariate Screening Approach.Materials (Basel, Switzerland) · 2026Article
- Torsional Behavior of Waste Fiber-Reinforced Concrete.Materials (Basel, Switzerland) · 2024Article
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Authors and funding
1 author.
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Abstract
With the recent and rapid development of concrete technologies and the ever-increasing use of concrete, adapting concrete to the specific needs and applications of civil engineering is necessary. Due to economic considerations and care for the natural environment, improving the methods currently used in concrete design is also necessary. In this study, the author used principal component analysis as a statistical tool in the concrete mix design process. Using a combination of PCA variables and 2D and 3D factors has made it possible to refine concrete recipes. Thirty-eight concrete mixes of different aggregate grades were analyzed using this method. The applied statistical analysis showed many interesting relationships between the properties of concrete and the content of its components such as the clustering of certain properties, showing dependence between the properties and the quantities of certain ingredients in concrete, and reducing noise in the data, which most importantly simplifies interpretation. This method of analysis can be used as an aid for concrete mix design.
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