| About this Abstract |
| Meeting |
MS&T24: Materials Science & Technology
|
| Symposium
|
Computational Materials for Qualification and Certification
|
| Presentation Title |
Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing |
| Author(s) |
Joshua D. Pribe, Patrick E. Leser, Brodan Richter, George Weber, Edward H. Glaessgen |
| On-Site Speaker (Planned) |
Joshua D. Pribe |
| Abstract Scope |
Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters for grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed on the process-structure model. Through GSA, the most important input parameters are identified using their influence on the statistical distributions of microstructural metrics that impact mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on the necessary experiments for quantifying and controlling PSP uncertainties, particularly those associated with the more challenging input parameters. |