2 papers
eess.SY2025
Harnessing On-Machine Metrology Data for Prints with a Surrogate Model for Laser Powder Directed Energy Deposition
Michael Juhasz, Eric Chin, Youngsoo Choi +2
In this study, we leverage the massive amount of multi-modal on-machine metrology data generated from Laser Powder Directed Energy Deposition (LP-DED) to construct a comprehensive…
cs.LG2024
Data-Driven, Parameterized Reduced-order Models for Predicting Distortion in Metal 3D Printing
Indu Kant Deo, Youngsoo Choi, Saad A. Khairallah +2
In Laser Powder Bed Fusion (LPBF), the applied laser energy produces high thermal gradients that lead to unacceptable final part distortion. Accurate distortion prediction is essen…