Successful prediction of the relevant mechanical properties of steels is of great importance to materials engineering. The aim of this research is to investigate the possibility of reducing the complexity of artificial neural networks-based prediction of total hardness of hypoeutectoid, low-alloy steels based on chemical composition, by introducing the specific Jominy distance as a new input variable. For prediction of total hardness after continuous cooling of steel (output variable), ANNs were developed for different combinations of inputs. Input variables for the first configuration of ANNs were the main alloying elements (C, Si, Mn, Cr, Mo, Ni), the austenitizing temperature, the austenitizing time, and the cooling time to 500 °C, while in the second configuration alloying elements were substituted by the specific Jominy distance. Comparing the results of total hardness prediction, it can be seen that the ANN using the specific Jominy distance as input variable (runseen = 0.873, RMSEunseen = 67, MAPE = 14.8%) is almost as successful as ANN using main alloying elements (runseen = 0.940, RMSEunseen = 46, MAPE = 10.7%). The research results indicate that the prediction of total hardness of steel can be successfully performed only based on four input variables: the austenitizing temperature, the austenitizing time, the cooling time to 500 °C, and the specific Jominy distance.

The purpose of this research is to upgrade the mathematical modeling and computer simulation of steel quenching. Based on theoretical analyses of physical processes that exist in quenching systems, the mathematical model for steel quenching is established and computer software is developed. The mathematical model of steel quenching is focused on physical phenomena, such as heat transfer, phase transformations, mechanical properties, and generation of stresses and distortions. The numerical procedure of computer simulation of steel quenching is divided into three parts: numerical calculation of transient temperature field, numerical calculation of phase change, and numerical calculation of the mechanical behaviors of steel during quenching. The numerical procedure is based on the finite volume method. Physical properties that were included in the model, such as heat conductivity coefficient, heat capacity, and surface heat transfer coefficient, were obtained by the inversion method based on the Jominy test results. By the completed algorithm, 3-D situation problems, such as the quenching of complex cylinders, cones, spheres, etc., can be simulated. The established model of steel quenching can be successfully applied in the practical usage of quenching.

This paper presents results of the corrosion investigations of specimens made from finished parts for the automotive industry, produced by high-pressure die casting and gravity die casting process of six Al-Si alloys (40000 series). Open circuit potential and potentiodynamic polarization measurements have been performed using a potentiostat with three-electrode set-up in 0.6 M NaCl naturally aerated solution. Microstructural characterization before and after electrochemical investigations has been carried out with optical microscope to establish the connection between microstructure and corrosion parameters of investigated alloys and to analyze and record surface changes of each sample due to electrochemical corrosion. All alloys show good corrosion resistance, which manifests with low values of corrosion rates, calculated from the corrosion current densities obtained from potentiodynamic polarization measurements. Differences in electrochemical behavior appear due to the distinctions in their chemical composition and microstructure. The type of casting process does not affect electrochemical behavior of Al-Si alloys.

The main goal of this paper is mathematical modelling and computer simulation of isothermal decomposition of austenite in steel. Mathematical modelling and computer simulation of isothermal decomposition of austenite nowadays is becoming an indispensable tool for the prediction of isothermal heat treatment results of steel. Besides that, the prediction of isothermal decomposition of austenite can be applied for understanding, optimization and control of microstructure composition and mechanical properties of steel. Isothermal decomposition of austenite is physically one of the most complex engineering processes. In this paper, methods for setting the kinetic expressions for prediction of isothermal decomposition of austenite into ferrite, pearlite or bainite were proposed. After that, based on the chemical composition of hypoeutectoid steels, the quantification of the parameters involved in kinetic expressions was performed. The established kinetic equations were applied in the prediction of microstructure composition of hypoeutectoid steels.

Low-alloy 42CrMo4 steel (AISI 4140) is a medium carbon steel, commonly used as a quenched and tempered steel. Because of its good mechanical properties, high tensile strength and toughness, 42CrMo4 is one of the widely used and investigated steels. In order to increase ductility even more, in addition to standard quenching and tempering, steel is often hardened by double quenching and tempering and austempering. The aim of this paper was to investigate the corrosion behaviour of 42CrMo4 steel after quenching and tempering, double quenching and tempering and austempering. For this purpose, microstructural characterization and electrochemical investigation after different hardening processes were performed. Microstructure of specimens was observed using optical microscopy and scanning electron microscopy. Open circuit potential and potentiodynamic polarization measurements of tempered specimens were carried out using computer-controlled potentiostat with three electrode set-up in 0.6 M NaCl naturally aerated solution. It was concluded that applied heat treatment processes increase the corrosion resistance of 42CrMo4 steel in comparison to normalized steel. In comparison to quenched and tempered steel, double quenching and tempering, as well as austempering, do not significantly change corrosion resistance of steel.

An increase in technical requirements related to the prediction of mechanical properties of steel engineering components requires a deep understanding of relations which exist between microstructure, chemical composition and mechanical properties. This paper is dedicated to the research of the relation between steel hardness with the microstructure, chemical composition and temperature of isothermal decomposition of austenite. When setting the equations for predicting the hardness of microstructure constituents, it was assumed that: (1) The pearlite hardness depends on the carbon content in a steel and on the undercooling below the critical temperature, (2) the martensite hardness depends primarily on its carbon content, (3) the hardness of bainite can be between that of untempered martensite and pearlite in the same steel. The equations for estimation of microstructure constituents’ hardness after the isothermal decomposition of austenite have been proposed. By the comparison of predicted hardness using a mathematical model with experimental results, it can be concluded that hardness of considered low-alloy steels could be successfully predicted by the proposed model.

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