| About this Abstract |
| Meeting |
2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023)
|
| Symposium
|
2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023)
|
| Presentation Title |
A Scientific Artificial Intelligence (Sci-AI)-based Concurrent Multiscale Simulation Framework for Accurate Temperature Prediction of Large-scale Metal Additive Manufacturing |
| Author(s) |
Lin Cheng |
| On-Site Speaker (Planned) |
Lin Cheng |
| Abstract Scope |
The broad applications of metal AM are hindered by the variability of mechanical performances due to time- and space-dependent thermal history. Although simulation models of multiple scales have been developed, either of them is able to provide accurate thermal history of large-scale production. This work aims to develop a concurrent multiscale framework capable of capturing the detailed melt pool dynamics in part-scale analysis. A Sci-AI model is to incorporate the in-situ data into the melt pool dynamics simulation for more accurate and efficient analysis. The computational cost of the Sci-AI model is at the microseconds level, allowing real-time coupling with part-scale analysis. This makes it possible to accomplish more accurate thermal history with detailed thermal fluid information for the part-scale fabrication and lays the foundation for concurrent multiscale modeling of metal AM process. Several numerical examples will be conducted to illustrate the performance of the proposed framework. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |