| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing: Process-induced Microstructures and Defects
|
| Presentation Title |
Porosity Predictions in Additively Manufactured Al-10Si-0.4Mg and Ti-6Al-4V Alloys Using a Geometric Model |
| Author(s) |
Akshatha Chandrashekar Dixith, Anthony G. Spangenberger, Diana A. Lados |
| On-Site Speaker (Planned) |
Akshatha Chandrashekar Dixith |
| Abstract Scope |
Additive manufactured parts contain fatigue crack-initiating defects even when fabricated using optimal processing parameters, limiting their use for structurally critical components in the transportation sector. Predictive models of pore formation are needed to bridge process-structure-performance gaps and provide a basis for mechanical behavior simulations. This research develops a computational methodology for predicting lack-of-fusion porosity size, shape, and distribution in laser powder bed fusion of Al-10Si-0.4Mg and Ti-6Al-4V. First, melt pool dimensions are determined from thermophysical models of the laser-workpiece interaction, and validated with experimental measurements. The dimensions are then used in a 3D geometric tiling model to predict lack-of-fusion pore morphology and distribution. Porosity measurements using optical microscopy and computed tomography are used to compare the simulated and experimental data and validate the model. The research will be further used for fatigue property predictions to support process optimization for high-integrity structural applications. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Modeling and Simulation, ICME |