About this Abstract |
| Meeting |
MS&T26: Materials Science & Technology
|
| Symposium
|
Advanced Materials for Harsh Environments
|
| Presentation Title |
Machine Learning Assisted Quantification of Microstructural Evolution and Multiscale Mechanical Properties of HP40Nb Reformer Alloy at 950°C |
| Author(s) |
Adnan Khan, Vasanth C. Shunmugasamy, Bilal Mansoor |
| On-Site Speaker (Planned) |
Adnan Khan |
| Abstract Scope |
Centrifugally cast austenitic stainless steels used as reformer tubes operate at 700°C - 1,000°C under service conditions leading to progressive microstructural degradation. In this study, HP40Nb was utilized as the model material to analyze the variations in microstructural and mechanical properties during exposure at 950℃. As-cast tube material was aged at 950℃ for up to 1600 h. Microstructural evolution was observed with respect to exposure time and compared with baseline as-cast microstructure. SEM/EDS and machine learning-assisted image analysis were used to quantify precipitate evolution, carbide coarsening, and phase transformations during thermal exposure. Thermal exposure promoted NbC-to-G phase transformation, Cr-rich carbide coarsening, and localized interdendritic microcrack initiation. Microhardness and nanoindentation revealed localized changes in matrix and precipitate mechanical responses during ageing. The results can improve understanding of the microstructural evolution and degradation mechanisms of austenitic stainless steels exposed to extreme service temperatures. |