About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
2026 Technical Division Student Poster Contest
|
| Presentation Title |
SPG-57: Predicting Shock Induced Spallation in Metal Microstructures: An EOS-Coupled Crystal Plasticity and Bayesian Inference Based Multiscale Framework |
| Author(s) |
S K Gargeya Bhamidipati, Somnath Ghosh |
| On-Site Speaker (Planned) |
S K Gargeya Bhamidipati |
| Abstract Scope |
Spallation is the dominant mode of material failure under high velocity impact and shock compression in polycrystalline metals, occurring through void nucleation driven by release waves at strain rates exceeding 10^4/s. This work presents the development of an equation-of-state (EOS) coupled crystal plasticity based multiscale model to predict spall response of aluminum alloys. Dislocation slip at high strain rates is modeled using a physics-based unified flow rule representing thermal-activation and phonon drag mechanisms, capturing temperature and strain rate dependence. The precursors governing void nucleation in the microstructure are identified using a Bayesian inference framework applied on a grain-resolved high-dimensional dataset generated using porous crystal plasticity simulations. The model captures experimentally observed EOS and shock Hugoniot relations. The multiscale framework developed in this work can simulate high strain rate tests such as Kolsky bar, plate impact and laser shock experiments, thereby revealing the dominant microstructural drivers of spall void nucleation. |
| Proceedings Inclusion? |
Undecided |
| Keywords |
Modeling and Simulation, ICME, Computational Materials Science & Engineering |