| About this Abstract |
| Meeting |
2022 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing Fatigue and Fracture: Developing Predictive Capabilities
|
| Presentation Title |
Prediction of Fatigue Life Based on the Microstructure and Porosity Distribution Using the Novel Computationally Efficient Multiscale Modeling |
| Author(s) |
Mohamed Elkhateeb, Yung C. Shin |
| On-Site Speaker (Planned) |
Yung C. Shin |
| Abstract Scope |
Additive manufacturing is mainly challenged by the existence of porosity and inhomogeneous microstructure in the fabricated parts. Prediction of the effects of such defects on the fatigue life requires very time-consuming and expensive experiments and multiscale mechanics models, which can be computationally cost-prohibitive for large structures. In this work, the novel scheme called extended mechanics of structure genome (XMSG) is used as a computationally efficient multi-scale homogenization scheme to predict the bulk behavior and fatigue life with considering porosity and microstructural details. In the XMSG, homogenization is conducted on a structure genome, which represents the smallest unit cells containing the basic microstructural and porosity details, and does need updates with porosity growth and coalescence. The predicted results showed a very good agreement with the experimental results with a drastic 5 orders of magnitude reduction in the computational time compared with the corresponding heterogeneous models-based finite element simulations. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Modeling and Simulation, Mechanical Properties |