Authors: Diana Hlushkova | V. M. Volchuk | Yurii Rukavishnikov
Source: Bulletin of Kharkov National Automobile and Highway University (article, 2025-11-30)
Field: Materials Science — Materials Chemistry

Forecasting the Mechanical Properties of Carbon Steels Annotation. Statement of the problem. Mechanical testing is a key tool for determining the properties of carbon steels; however, direct methods, such as tensile or hardness testing, are often labor-intensive, costly, and require specialized equipment. These methods are complicated by the need for sample preparation, lengthy testing times, and significant expenses, which limit their application in mass production or rapid quality control. Furthermore, the structure of carbon steels undergoes significant changes under the influence of various types of heat treatment, which affects their mechanical properties. This highlights the need for the development of new, more efficient approaches to evaluating the structure and properties of metals, enabling rapid and accurate prediction of the behavior of carbon steels under various conditions. Purpose and setting of the task. The aim is to develop a method for evaluating the hardness of carbon steel based on the analysis of austenite decomposition products using multifractal analysis. To achieve this objective, the following tasks must be accomplished: 1. Conduct heat treatment of carbon steel and perform microstructural analysis after heat treatment and cooling in various media. 2. Perform multifractal analysis of lamellar pearlite, martensite, and retained austenite to establish a correlation with the hardness properties of carbon steel. 3. Enable the prediction of carbon steel hardness by constructing mathematical models using multifractal indicators of the steel structure. Materials and Research Methods. The material selected for the study was U8 carbon steel, which is widely used for manufacturing general-purpose tools subjected to dynamic loads during operation. This contributes to the emergence of structural heterogeneity and significantly affects their operational characteristics. The samples were prepared with a length of 40 mm and a cross-section of 5×5 mm. Table 2 presents the heat treatment regimes and hardness values. Three heat treatment regimes were selected for the study: 780°C with furnace cooling (annealing), 780°C with oil quenching, and 780°C with water quenching. The holding time during heating in the furnace was set to 30 minutes for all samples. To ensure the reliability of the results, three hardness measurements were conducted in each of the specified sample regions, from the center to the edge. Research material and methods. he decrease in the homogeneity of lamellar pearlite from the center to the edge of Sample 1 is associated with an increase in local defects, as evidenced by the reduction in the fractal dimension of pearlite from 1.55 at the center to 1.51 at the edges. This correlates with the change in hardness, which increases from 36 HRC at the center to 40 HRC at the edge. The obtained data indicate that hardness, as a local characteristic of the microvolume of the carbon alloy, depends on the spatial defect of the microstructure, expressed in the dimensional units of multifractal analysis. The microstructure of Sample 2 (oil quenching) consists of pearlite, which forms along the boundaries of former austenite grains (dark areas), and martensite (light areas). The homogeneity of this structure is determined by the semi-diffusional transformation of austenite with partial martensitic transformation, accompanied by diffusional redistribution of carbon. Variations in cooling rates across the sample’s cross-section contributed to changes in the phase composition: the pearlite fraction decreased from 16% at the center to 7% at the edge, while the martensite fraction increased. The microstructure of Sample 3 (water quenching) consists of lamellar martensite (approximately 92%, dark areas) and retained austenite (approximately 8%, light areas) across the entire cross-section. The decrease in martensite homogeneity from the center to the edge of the sample may be attributed to an increase in local defects at the substructural level, associated with differences in cooling rates. This is confirmed by the reduction in the fractal dimension of martensite from 1.97 at the center to 1.74 at the edge. Substructural changes affecting defects include an increase in dislocation density, an increase in second-order internal stresses, and a reduction in subgrain sizes while maintaining stable a-Fe lattice parameters. These changes correlate with an increase in hardness from 71 HRC at the center to 75 HRC at the edge, indicating an improvement in strength properties from the center to the surface of the sample. The obtained results demonstrate the high sensitivity of the hardness of carbon alloys to homogeneity characteristics determined through multifractal analysis. Specifically, changes in homogeneity correlate with hardness due to local defects and phase composition. This confirms that multifractal analysis serves as an effective tool for the quantitative evaluation of microstructure and the prediction of material properties. Conclusions. The study explores the potential of using multifractal analysis for the quantitative evaluation of the morphology of structural components in carbon alloys subjected to various heat treatment regimes. The homogeneity of the structure, expressed through spatial defects in dimensionality indicators, is determined, and the maximum sizes of regions with homogeneous distribution of structural elements are established. A comparison of homogeneity indicators with hardness (HRC) revealed their correlation, attributed to changes in local microstructural defects. In all samples, a decrease in homogeneity from the center to the edge was observed, associated with an increase in defects (e.g., dislocation density and internal stresses) due to differences in cooling rates. For Sample 1, the fractal dimension of pearlite decreased from the edge to the center from 1.55 to 1.51, while for Sample 3, the fractal dimension of martensite decreased from 1.97 at the edge to 1.74 at the center, correlating with an increase in hardness from 36 to 40 HRC for Sample 1 and from 71 to 75 HRC for Sample 3, respectively. It is demonstrated that multifractal analysis of the microstructure surpasses traditional methods of quantitative metallography in sensitivity to substructural changes and the geometric complexity of the microstructure, making it a promising tool for evaluating the physical-mechanical properties of materials. Carbon fibers ; Austenite ; Carbon steel ; Lamellar structure ; Material properties ; Structural material ; Ultimate tensile strength ; Decomposition Material Properties and Failure Mechanisms ; Machine Learning in Materials Science ; Surface Treatment and Coatings