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The increased thermal efficiency of fossil power plants calls for the development of advanced creep-resistant alloy steels like T92. In this study, microstructures found in the heat-affected zone (HAZ) of a T92 steel weld were simulated to evaluate their creep-rupture-life at elevated temperatures. An infrared heating system was used to heat the samples to 860 °C (around AC1), 900 °C (slightly below AC3), and 940 °C (moderately above AC3) for one minute, before cooling to room temperature. The simulated specimens were then subjected to a conventional post-weld heat treatment (PWHT) at 750 °C for two hours, where both the 900 °C and 940 °C simulated specimens had fine grain sizes. In the as-treated condition, the 900 °C simulated specimen consisted of fine lath martensite, ferrite subgrains, and undissolved carbides, while residual carbides and fresh martensite were found in the 940 °C simulated specimen. The results of short-term creep tests indicated that the creep resistance of the 900 °C and 940 °C simulated specimens was poorer than that of the 860 °C simulated specimens and the base metal. Moreover, simulated T92 steel samples had higher creep strength than the T91 counterpart specimens.

Additive manufacturing (AM) has emerged as a crucial technology in recent decades, particularly within aerospace industry. However, the thermally cyclic nature of these processes introduce significant variations and defects in microstructure, which can adversely affect final part performance and hinder the widespread adoption of the technology. Traditionally, characterization of AM parts has relied on conventional bulk testing methods, which involve analyzing many samples to gather sufficient data for statistical analysis. Unfortunately, these methods are unable to account for local nanoscale variations in material properties caused by the microstructure, as they measure a single averaged property for each tested sample. In this work, we use AM Inconel 718 as a model system in developing a novel approach to correlate nanomechanical properties obtained through nanoindentation with microstructure obtained through electron backscatter diffraction (EBSD). By associating mechanical properties obtained from each indent with the corresponding crystallographic direction measured with EBSD, we calculate the weighted average hardness and modulus for each orientation. This enables us to generate inverse property figure maps depicting the relationship between mechanical properties and crystallographic direction. Our method yields results in good agreement with literature when calculating the part modulus and hardness. Furthermore, it effectively captures nanoscale variations in properties across the microstructure. The key advantage of this methodology is its capability to rapidly test a single AM part and generate a large dataset for statistical analysis. Complementing existing macroscale characterization techniques, this method can help improve AM part performance prediction and contribute to the wider adoption of AM technologies.