4 papers
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…
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…
A Data-Driven, Non-Linear, Parameterized Reduced Order Model of Metal 3D Printing
Aaron L. Brown, Eric B. Chin, Youngsoo Choi +2
Directed energy deposition (DED) is a promising metal additive manufacturing technology capable of 3D printing metal parts with complex geometries at lower cost compared to traditi…
First-Principles Studies of the Metallization and the Equation of State of Solid Helium
Saad Antoun Khairallah, Burkhard Militzer
The insulator-to-metal transition in solid helium at high pressure is studied with first-principles simulations. Diffusion quantum Monte Carlo (DMC) calculations predict that the b…