Influence of Al/Ti Ratio and Ta Concentration on the As-Cast Microstructure, Phase Composition, and Phase Transformation Temperatures of Lost-Wax Ni-Based Superalloy Castings

The as-cast microstructure, alloying element segregation, solidification behavior, and thermal stability of model superalloys based on Inconel 740 with various Al/Ti ratios (0.7, 1.5, 3.4) and Ta (2.0, 3.0, 4.0 wt%) concentrations were investigated via ThermoCalc simulations, scanning and transmission electron microscopy, energy-dispersive X-ray spectroscopy, dilatometry, and differential scanning calorimetry. The solidification of the superalloys began with the formation of primary γ dendrites, followed by MC carbides. The type of subsequently formed phases depended on the superalloys’ initial Al/Ti ratio and Ta concentration. The results obtained from solidification simulations were compared to the obtained microstructures. For all castings, the dendritic regions consisted of fine γ′ precipitates, with their size mainly depending on the initial Al/Ti ratio, whereas in the interdendritic spaces, (Nb, Ta, Ti)C carbides and Nb-rich Laves phase precipitates were present. In high Al/Ti ratio superalloys, β-NiAl precipitates, strengthened by η and α-Cr phases, were observed. Based on dilatometric results, the dissolution of γ′ precipitates was accompanied by a substantial increase in the coefficient of thermal expansion. The end of the dilatation effect took place around the γ′ solvus temperature, as determined via calorimetry. Moreover, the bulk solidus temperature was preceded by the dissolution of the Laves phase, which may be accompanied by local melting

Developing a Methodology for Building the Knowledge Base and Application Procedures Supporting the Process of Material and Technological Conversion

The article presents the developed IT solutions supporting the material and technological conversion process in terms of the possibility of using the casting technology of selected alloys to produce products previously manufactured with the use of other methods and materials. The solutions are based on artificial intelligence, machine learning and statistical methods. The prototype module of the information and decision-making system allows for a preliminary assessment of the feasibility of this type of procedure. Currently, the selection of the method of manufacturing a product is based on the knowledge and experience of the technologist and constructor. In the described approach, this process is supported by the proprietary module of the information and decision-making system, which, based on the accumulated knowledge, allows for an initial assessment of the feasibility of a selected element in a given technology. It allows taking into account a large number of intuitive factors, as well as recording expert knowledge with the use of formal languages. Additionally, the possibility of searching for and collecting data on innovative solutions, supplying the knowledge base, should be taken into account. The developed and applied models should allow for the effective use and representation of knowledge expressed in linguistic form. In this solution, it is important to use methods that support the selection of parameters for the production of casting. The type, number and characteristics of data have an impact on the effectiveness of solutions in terms of classification and prediction of data and the relationships detected