Study of the influence of the composition and structure of Ст3пс steel on hardness
Formulation of the problem. The use of indirect methods of quality control of metal rolling is due to many factors, among which the influence of the chemical composition and technological regimes should be noted. These factors affect the structure and the mechanical characteristics, in particular, low carbon steels. In the work for the prediction of hardness indicators of Ст3пс steel, it is proposed to apply the methodology of planning experiments, taking into account the influence of elements of chemical composition and structure. To estimate the ferrite-pearlite structure, it is proposed to use the fractal formalism, the use of which allows you to track changes in the structure by determining the fractal dimension of its elements. Materials and methods. Using the methodology of planning experiments, the effect of the chemical composition and structure on the mechanical properties of low-carbon Ст3пс low-alloyed steel was investigated. Results. By implementing the experiment planning matrix, a mathematical model was obtained for evaluating the hardness of Ст3пс steel, taking into account the influence of elements of chemical composition and the fractal dimension of perlite. The model is adequate according to the criteria of Cochran's and Fisher. Based on the analysis of the coefficients of the regression equation, a histogram of the influence of the elements of the chemical composition of the studied steel on the hardness indicators was constructed. The growth of the fractal dimension of perlite from 1,785 to 1,946 with an increase in the carbon content from 0,14 to 0,22 % was recorded, which indicates the possibility of its use in assessing the structure of low-carbon steels. Conclusions. A method for assessing the hardness of St3ps steel has been developed, taking into account the influence of elements of chemical composition and fractal dimension of perlite. The results indicate the prospects for the application of the theory of fractals in the prediction of the mechanical properties of low-carbon steels.