About this Abstract |
Meeting |
2022 TMS Annual Meeting & Exhibition
|
Symposium
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Algorithm Development in Materials Science and Engineering
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Presentation Title |
Microstructure and Porosity Predictions in Additively Manufactured Ti-6Al-4V Alloys Using a Hierarchical Modeling Approach |
Author(s) |
Bonnie Whitney, Akshatha Chandrashekar Dixith, Anthony G. Spangenberger, Diana A. Lados |
On-Site Speaker (Planned) |
Akshatha Chandrashekar Dixith |
Abstract Scope |
The additive manufacturing (AM) technologies are rapidly changing the manufacturing paradigm by enhancing component design flexibility while lowering development time and cost. Computational tools are needed to optimize AM parts for high-integrity structural applications, which require accurate microstructure and porosity predictions. This research proposes a hierarchical computational methodology for laser powder bed fusion of Ti-6Al-4V to link key processing-structure parameters. The approach integrates component-scale thermal finite element simulations (spatial-temporal temperature histories), melt pool cellular automaton simulations (prior beta grain morphology), and solid-state phase field transformations (alpha phase morphology/orientation). In parallel, melt pool dimensions from thermal simulations were used to predict the morphology and distribution of lack-of-fusion pores using a geometric model. An extensive experimental build was judiciously developed and characterized to validate and fine-tune the microstructure and porosity predictions. The results will be presented and discussed from the perspective of future integration in mechanical properties modeling. |
Proceedings Inclusion? |
Planned: |