The chemical composition of standard Inconel 740 superalloy was modified by changes in the Al/Ti ratio (0.7, 1.5, 3.4) and addition of Ta (2.0, 3.0, 4.0%). Remelted Inconel 740 (A0) and nine variants with various chemical compositions were fabricated by lost-wax casting. The microstructure, microsegregation, phase transformation temperatures, thermal expansion coefficients and hardness of the superalloys were investigated by scanning electron microscopy, energy dispersive X-ray spectroscopy, differential scanning calorimetry, dilatometry and Vickers measurements. Typical dendritic microstructure was revealed with microsegregation of the alloying elements. Segregation coefficient ki for Ti, Nb and Ta did not exceed unity, and so precipitates enriched mainly in these elements were found in interdendritic spaces. The Nb-rich blocky precipitates, MC carbides, MN nitrides, oxides, and fine γ’ was in all modified castings. Presence of other microstructural features, such as Ti-rich needles, eutectic γ-γ’ islands, small Al-rich and Cr-rich precipitates depended on the casting composition. The lowest solidus and liquidus temperatures were observed in superalloys with a high Al/Ti ratio. Consequently, in A7–A9 variants, the solidification range did not exceed 100 °C. In the A0 variant the difference between liquidus and solidus temperature was 138 °C. Hardness of all modified superalloys was at least 50% higher than for the remelted Inconel 740 (209 HV10).
The aim of the work is to investigate the effectiveness of selected classification algorithms and their extensions in assessing microstructure of castings. Experiments were carried out in which the prepared algorithms and machine learning methods were tested in various conditions and configurations, as well as for various input data, which are photos of castings (photos of the microstructure) or information about the material (e.g., type, composition). As shown by the literature review, there are few scientific papers on this subject (i.e., in the use of machine learning to assess the quality of the microstructure and the obtained strength properties of cast iron). The effectiveness of machine learning algorithms in assessing the quality of castings will be tested using the most universal methods. Results obtained by classic machine learning methods and by neural networks will be compared with each other, taking into account aspects such as interpretability of results, ease of model implementation, algorithm simplicity, and learning time.
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.
Nickel alloys belong to the group of most resistant materials when used under the extreme operating conditions, including chemically aggressive environment, high temperature, and high loads applied over a long period of time. Although in the global technology market one can find several standard cast nickel alloys, the vast majority of components operating in machines and equipment are made from alloys processed by the costly metalworking operations. Analysis of the available literature and own studies have shown that the use of casting technology in the manufacture of components from nickel alloys poses a lot of difficulty. This is due to the adverse technological properties of these alloys, like poor fluidity, high casting shrinkage, and above all, high reactivity of liquid metal with the atmospheric air over the bath and with the ceramic material of both the crucible and foundry mold. The scale of these problems increases with the expected growth of performance properties which these alloys should offer to the user. This article presents the results of studies of physico-chemical interactions that occur between the H282alloy melt and selected refractory ceramic materials commonly used in foundry. Own methodology for conducting micro-melts on a laboratory scale was elaborated and discussed. The results obtained have revealed that the alumina-based ceramics exhibits greater reactivity in contact with the H282 alloy melt than the materials based on zirconium compounds. In the conducted experiments, the ceramic materials based on zirconium silicate have proved to be a much better choice than the zirconia-silica mixture. Regardless of the type of the ceramic materials used, the time and temperature of their contact with the nickel alloy melt should always be limited to an absolutely necessary minimum required by the technological regime.
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