| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing Modeling, Simulation and Machine Learning
|
| Presentation Title |
F-74: Crystal Plasticity Modeling for the Prediction of Mechanical Properties of Laser Powder Bed Fusion AlSi10Mg Parts |
| Author(s) |
Nathan March, Dayalan R. Gunasegaram |
| On-Site Speaker (Planned) |
Dayalan R. Gunasegaram |
| Abstract Scope |
The state-of-the-art modeling technique that combines Crystal Plasticity (CP) constitutive models with Fast Fourier Transform (FFT)-based numerical solvers is used in the micromechanical modeling of additively manufactured (AM) metal parts. We use this technique to develop a methodology for the prediction of location-dependent mechanical properties on AlSi10Mg parts made using laser powder bed fusion. Crucially, our methodology overcomes some of the significant computational challenges presented by the spatially varying, anisotropic microstructures found on AM parts. Additionally, it enables accurate and efficient simulations which capture both the complex, hierarchical structures present in AlSi10Mg and the stochastic variation inherent in the mechanical properties of AM parts. Predictions are validated against experimental results. Our contribution, rooted in the ICME paradigm, relates to a crucial link in the process-structure-property-performance relationship of AM parts. Also, while we demonstrate our technique on AlSi10Mg, our multiscale methodology can be applied to other alloy systems. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Mechanical Properties, Other, Other |