| Author(s) |
Rana Bakhtiyarzade, Nate Bianco, Tara Wagoner, Brian Thurston, Alexander Bandar, Michael A. Groeber, Dennis Dimiduk, Glenn S. Daehn, Stephen R. Niezgoda |
| Abstract Scope |
Agility Forge, a robotic blacksmithing platform, enables controlled hot open-die forging under variable thermal conditions, capturing full-field temperature, force, displacement, and strain histories during deformation. A “phantom bar” featuring varied geometries (cylinder, box, cone, sphere) was forged to generate high-fidelity, location-specific datasets for model calibration and validation. Detailed process histories—including force, strain, temperature, rotation angles, and number of hits—inform a Model-Based Material Definition (MBMD) framework that links processing to structure and properties through the P–S–P–P (Processing- structure – properties- performance) chain. Grain morphology, crystallographic texture, and residual stress are reconstructed with uncertainty quantification, enabling voxel-level strength, hardness, and grain size prediction. Experimental coupons support validation and iterative refinement of model predictions, contributing to updated design allowables. By anchoring simulation in real thermal and deformation histories, this work establishes a scalable verification and validation loop that reduces reliance on destructive testing and supports certification and qualification of complex, non-standard forged geometries. |