About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Materials Processing Fundamentals: Towards Sustainable Process Modeling, Design, and Operation
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| Presentation Title |
Probabilistic Spot-Melting Scan Strategy for Microstructure Engineering in Electron Beam Additive Manufacturing |
| Author(s) |
Salman Mohammad Ismail, Toan Truong, Haojun You, Mohsen Taheri Andani, Guillermo Aguilar |
| On-Site Speaker (Planned) |
Salman Mohammad Ismail |
| Abstract Scope |
Additive manufacturing enables the design of scan strategies that influence thermal histories and microstructure, providing opportunities to improve process robustness and component performance. This work investigates a probabilistically generated scan strategy in which each successive melt point is sampled from a normal distribution centered on the previous point, producing spatially varying beam paths that modify local thermal gradients and cooling rates. Applied to Ti-6Al-4V in electron beam powder bed fusion, this approach enables exploration of scan path designs that depart from conventional deterministic patterns while influencing solidification behavior. A transient thermal conduction model employing adaptive Gaussian quadrature is used to capture the rapid heating and cooling cycles associated with spot melting. The resulting thermal histories are analyzed to assess conditions governing the columnar-to-equiaxed transition using established solidification criteria. By combining probabilistic scan path generation with predictive thermal modeling, the framework enables computational evaluation of scan strategies that can reduce reliance on empirical parameter exploration and improve the consistency of microstructure control. The results highlight how modeling-driven scan strategy design can support more efficient and robust additive manufacturing workflows while enabling targeted microstructure engineering in Ti-6Al-4V components. |
| Proceedings Inclusion? |
Planned: |