| About this Abstract |
| Meeting |
2022 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing Fatigue and Fracture: Developing Predictive Capabilities
|
| Presentation Title |
Predictive Modeling of Fracture in Anisotropic and Porous Materials |
| Author(s) |
Amine Benzerga, Vigneshwaran Radhakrishnan |
| On-Site Speaker (Planned) |
Vigneshwaran Radhakrishnan |
| Abstract Scope |
Additively manufactured metals often exhibit directional mechanical properties as well as residual processing-induced porosity. Unless production cost is not a factor, anisotropy and porosity are both unavoidable attributes of AM products. Here, recent progress in first-principles modeling of failure in materials with initial porosity is used to lay out a methodology for predictive modeling of failure in AM. The aim is to assess the effects of porosity and plastic anisotropy, taken separately or combined, on a stress-state dependent measure of strain to failure. Published experimental data on materials with varying ductility levels is used to demonstrate the predictive capability of the proposed modeling framework. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Modeling and Simulation, Mechanical Properties |