DOI: https://doi.org/10.36719/2789-6919/54/150-154
Vasif Abbasov
Azerbaijan State Oil and Industry University
PhD student
https://orcid.org/0009-0009-1972-5793
vasifabasov636@gmail.com
Construction of a Regression Model for the Strength Indicators
of Concrete Mixes
Abstract
The present article is devoted to the development of regression models for predicting the strength characteristics of concrete mixtures. The study identifies the main material and technological factors affecting the compressive strength of concrete and analyzes their statistical characteristics. Parameters such as cement content and type, water-cement ratio, fine and coarse aggregate proportions, as well as chemical and mineral admixtures are evaluated using a multivariable regression approach.
The theoretical foundations of regression analysis are discussed, and the applicability of linear and nonlinear regression models in concrete technology is demonstrated.
The stages of model development, including experimental data collection, selection of significant variables, estimation of regression coefficients, and assessment of model adequacy using statistical criteria, are described in detail. The results indicate that the developed regression model provides reliable predictions of concrete strength and allows for a reduction in the number of laboratory tests.
The findings of the study have significant practical importance for optimizing concrete mix design, reducing material consumption, and ensuring consistent product quality. Moreover, the application of regression models contributes to scientifically based decision-making processes in concrete production and supports the development of modern construction materials.
Keywords: concrete mixtures, concrete strength, regression model, statistical analysis, concrete technology, multivariable modeling