Abstract

The processes of structure formation of composite building materials (KSM) on different polymer binders are presented. It is shown that one of the most significant components of KSM are fillers, which help to improve their structural and operational characteristics. This work is devoted to the analysis of the results of an experimental study of the properties of epoxy composites with fillers having various elastic-plastic and strength properties. The research was carried out in three stages: at the first stage, studies were conducted aimed at assessing the influence of the nature of the filler on the curing processes of KSM; at the second, the influence of the type of filler and its quantitative content on the strength of composites was established, at the third, compositions were optimized using fillers with different indicators of grain composition and elastic-plastic properties. Powders of glass, dolomite, thermolite, and diatomite were considered as fillers at the first and second stages of the research, and powders of glass, ceramics, and chalk were considered at the second stage. The research at the third stage was carried out using mathematical methods of experiment planning with the construction of a planning matrix for a complete factor experiment and the determination of the values of the response functions relative to the encoded factors. The physico-mechanical properties, degree of curing, and chemical resistance of filled epoxy CCM have been established. On the basis of artificial neural networks, the maximum properties of the studied composites with fillers were determined. An assessment of structural properties based on rank correlation is also proposed. The results of the research can be used to predict the properties of KSM, as well as to clarify the extreme parameters of the properties. The dependences of changes in the properties of polymer composites on the surface characteristics, the dispersion of fillers and the degree of filling were established; preferred fillers for epoxy composites were determined; fillers were determined to assess the effect of elastic surface properties of composites, allowing to improve the strength and deformability of polymer composites; regression models were obtained based on a complete factorial experiment; an assessment of the «structural stability» of the studied composites using Pearson, Kendall, Spearman rank correlation; On the basis of artificial neural networks, the extreme properties of the studied composites with fillers were determined, neural networks.

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