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The ordered γ′-(Ni, Cu)3Al is a crucial strengthening phase that improves the high-temperature resistance of Cu-based alloys, so it is important to predict the kinetic evolution of the composition and microstructure of the phase for high-temperature applications. Herein, this paper discusses the temporal evolution of the composition and coarsening of the γ′ phase in a model ternary Cu50Ni37.5Al12.5 (at%) alloy during isothermal aging at 600, 700, 800, and 900 °C for 1–36 h. It is found that the γ′ phase composition evolves linearly toward a binary γ′ phase as the aging time increases during the process of aging at 800 and 900 °C, which cannot be predicted by the ternary phase diagrams alone. Meanwhile, through the utilization of the aforementioned linear law, the γ phase composition can be predicted at a given temperature within the alloy by determining the volume fraction of the γ′ phase. Additionally, the activation energy for coarsening decreases, and the coarsening rate of the γ′ phase increases owing to the higher diffusion rate of Cu at high temperatures. The addition of microalloying elements with strong enthalpic interactions is beneficial for reinforcing the structural stability of the γ′ phase. This work provides a simple method for the compositional analysis and performance prediction of Cu–Ni–Al alloys at elevated temperatures and sheds light on the subsequent compositional design and optimization of Cu-based high-temperature alloys. [ABSTRACT FROM AUTHOR]

Methods of economical alloying of high pipe steels were considered in the paper. Due to the large environmental, energy, and economic issues in the destruction of the pipeline, the quality of steel pipes is very important. The method described in this article is considered to be relevant not only for pipe steels but also for high-strength steels used in shipbuilding, bridge construction, etc. Review mechanisms of strengthening microalloyed steels were carried out in this work. Schema evolution of the microstructure of microalloyed steels was discussed. The influence of alloying elements in steel by means of optimal process parameters of thermomechanical rolling was analyzed. There are two methods of mathematical modeling used in the study: artificial neural networks (ANNs) which are based on the multilayered perceptron to select the optimal chemical composition and finite element analysis to optimize the process parameters. An experimental dataset was used to train multilayer perceptron (MLP) networks to allow for prediction of the yield strength, tensile strength, and elongation of steel. Due to large availability, low cost, and high accuracy of the results, these methods are considered to be the most promising ones. The mathematical model for calculating mechanical properties of a rolling pipe has been developed. Two ways to reduce the cost of a hot-rolled plate made of microalloyed steels were developed. There has been developed the complex of replacement technological impact which can make it possible to replace or reduce the amount of expensive chemical elements (vanadium, nickel, copper, manganese, chromium, and niobium) without loss of quality. [ABSTRACT FROM AUTHOR]