About this Abstract |
Meeting |
2022 TMS Annual Meeting & Exhibition
|
Symposium
|
Algorithm Development in Materials Science and Engineering
|
Presentation Title |
Calibrating Uncertain Parameters in Melt Pool Simulations of Additive Manufacturing |
Author(s) |
Gerry L. Knapp, John Coleman, Miroslav Stoyanov, Alex Plotkowski |
On-Site Speaker (Planned) |
Gerry L. Knapp |
Abstract Scope |
Melt pool scale models of additive manufacturing (AM) processes can help elucidate process-structure-property relationships for AM parts. However, the predictive capability of these models is limited by uncertainties in experimental conditions and model parameters. Here, a method is proposed to calibrate uncertain parameters used in a continuum model for powder bed fusion AM. Two different model fidelities are examined: a higher fidelity version that considers fluid flow in the melt pool and a lower fidelity version that neglects fluid flow. The Tasmanian package was used for automated surrogate construction and calibration of melt pool width and depth to within 10% of the NIST AMB2018-02 dataset melt pool geometries. It is demonstrated that the heat source dimensions in the lower fidelity model can be calibrated to approximate the effects of fluid flow in the melt pool. This work was supported by the Exascale Computing Project. |
Proceedings Inclusion? |
Planned: |
Keywords |
Additive Manufacturing, Modeling and Simulation, Solidification |