| About this Abstract |
| Meeting |
2023 TMS Annual Meeting & Exhibition
|
| Symposium
|
Late News Poster Session
|
| Presentation Title |
A-66: Fatigue Life Predictions of Additive Friction Stir Deposition Repairs using a Smooth Particle Hydrodynamic Model |
| Author(s) |
Nick Palya |
| On-Site Speaker (Planned) |
Nick Palya |
| Abstract Scope |
A Smooth Particle Hydrodynamic (SPH) simulation of an Additive Friction Stir Deposition (AFSD) repair was used to inform a multiscale approach to predicting the fatigue life of a high strength aluminum alloy. The AFSD process is a solid-state layer-by-layer additive manufacturing approach in which a hollow tool containing feedstock is used to deposit material. Elevated temperatures and strain rates associated with severe plastic deformation processes (SPDP) make accurate collection of experimental data within AFSD difficult. An understanding of the evolving microstructures is necessary to predict material performance. Without the ability to experimentally determine material history within the AFSD process, a smooth particle hydrodynamic (SPH) model was employed to predict the thermomechanical history. This SPH simulation of AFSD allowed material history predictions to be used in with existing microstructure and fatigue models to predict the fatigue life of an AFSD repair in a 7075 aluminum alloy. |
| Proceedings Inclusion? |
Undecided |
| Keywords |
Additive Manufacturing, Aluminum, Computational Materials Science & Engineering |