About this Abstract |
| Meeting |
2026 AWS Professional Program
|
| Symposium
|
2026 AWS Professional Program
|
| Presentation Title |
Computational Alloy Design of P91-Type Steels for Virtual Manufacturing and Qualification |
| Author(s) |
Yousub Lee, Bhagya Prabhune, Rangasayee Kannan, Yukinori Yamamoto, William Carter, Chris Masuo, Aslan Nasirov, Andrzej Nycz, Srdjan Simunovic |
| On-Site Speaker (Planned) |
Yousub Lee |
| Abstract Scope |
Ferritic-martensitic steels containing 9-12 wt.% Cr are key structural materials for harsh environments in fossil and nuclear energy applications. To optimize F-M steel made using wire-arc Direct Energy Deposition (DED), adjusting the phase transformation temperature and material properties by modifying P91’s composition is necessary. Current parameter development and part qualification strategies in wire-arc DED such as operator-driven trial-and-error or extensive experiments are a major bottleneck for rapid adoption of new alloys and scaling of critical parts. Nonlinear physical interactions among alloy composition, energy input, process parameters, and part geometry make a prediction highly complicate and intensive. With broad compositional specifications (13-18 independent elements), AM printability and performance can vary largely. One specification may lead to cracking, poor high-temperature properties, or weak deformation resistance depending on actual composition within the specification window.
In this research, we investigated alloy-process-material-microstructure-performance relationships in the high-dimensional composition spaces of P91. Using Latin Hypercube Sampling, more than 1000 candidate compositions were generated within ASME/ASTM specification ranges and evaluated using JMatPro and Thermo-Calc to predict the thermophysical and mechanical properties. Composition-induced variability was quantified using coefficient of variation. The results showed that the coefficient of thermal expansion shows the highest overall sensitivity to composition followed by specific heat. A normalized “composite score” combining distortion score, high-temperature score, and cracking score, ranked candidate alloys for the initial screening of candidate compositions. Based on this score, the top 10 balanced compositions were chosen and evaluated through multi-physics simulations to assess their performance in practical manufacturing scenarios. Noticeable changes in G/R space indicate that composition strongly affects thermophysical behavior and microstructure evolution during wire-arc DED. Ongoing work will evaluate distortion and residual-stress responses using experimentally relevant process parameters. |
| Proceedings Inclusion? |
Undecided |