| About this Abstract |
| Meeting |
MS&T21: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing of Metals:
ICME Gaps: Material Property and Validation Data to Support Certification
|
| Presentation Title |
Determining Data Requirements to Quantify Porosity in the Laser Powder Bed Fusion Process |
| Author(s) |
Mahya Shahabi, Caitlin M. Kean, Adrianna Y. Yuen, Anthony D. Rollett, Sneha Prabha Narra |
| On-Site Speaker (Planned) |
Sneha Prabha Narra |
| Abstract Scope |
Data-driven quantification of microstructure in additively manufactured parts helps establish process-structure-property relations. For instance, fatigue resistance is governed by the upper tail of the porosity distribution. However, the amount of data required to accurately populate the porosity distribution is still unknown. Towards addressing this gap, this talk discusses the data required to quantify porosity in the laser powder bed fusion (L-PBF) additively manufactured parts. 2D porosity data obtained from cross-sectional microscopy was used as an example. The minimum required number of pores was identified for multiple L-PBF specimens (varying porosity levels) to achieve a representative Generalized Pareto distribution to describe the upper tail. Our results confirm the intuition that the data required to characterize part porosity is primarily determined by the quality of the sample and the required precision of the model. Methods described here can also be applied to 3D porosity data and features such as grain size. |