About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Algorithms Development in Materials Science and Engineering
|
| Presentation Title |
Thermodynamically-Guided Pseudo-Fluid Deposition Algorithm for Metal Additive Manufacturing: A Voxel-Based Framework Integrating Surface Energy Minimization and Mass Redistribution |
| Author(s) |
Hamed Hosseinzadeh |
| On-Site Speaker (Planned) |
Hamed Hosseinzadeh |
| Abstract Scope |
We introduce a voxel-based pseudo-fluid deposition algorithm for Directed Energy Deposition (DED) that enables precise control of thermal gradients and thermal rates critical for microstructural and mechanical simulations. Molten voxels are deposited according to a mass-feed-rate-driven rule (g/s), with their position refined via a local surface energy minimization heuristic. This algorithm mimics capillary stabilization by evaluating neighborhood occupancy and relocating voxels to maximize surface bonding, guided by a pseudo-energy gradient. We further integrate simplified surface diffusion equations to approximate redistribution under thermal fields without full CFD. The resulting model captures realistic heating/cooling rates and thermal gradients, enabling accurate prediction of solidification behavior, residual stress, and microstructural features. This physics-guided approach advances high-fidelity simulation for AM, with direct relevance to CALPHAD-informed phase-field modeling, digital twins, and mesoscale analysis. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Computational Materials Science & Engineering, Additive Manufacturing, Modeling and Simulation |