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 (r_unseen = 0.873, RMSE_unseen = 67, MAPE = 14.8%) is almost as successful as ANN using main alloying elements (r_unseen = 0.940, RMSE_unseen = 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.

In this paper, the effect of different hardness filler materials and sequence of welding on the ballistic performance has been investigated. Also, besides the optimization of the ballistic properties, other mechanical testing was carried out in order to achieve wanted mechanical properties along the entire welded joint. The experimental work includes macrostructure analysis, ballistic testing, and hardness testing of steel welded joint. The base material used in the experiment were ARMOX® 500T plates. In this experiment 3 different filler materials were used. Based on the testing results, it was found out that best ballistic performance of the welded joint is achieved if capping layer is welded with a hardfacing filler material. This distributes the impact energy to a greater area and transfers it to the lower hardness weld layer underneath which then absorbs the rest of the energy.

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.

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.