4 citations · 8 across the 3 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2021★ 3 cited
Comprehensive process-molten pool relations modeling using CNN for wire-feed laser additive manufacturing
Noopur Jamnikar, Sen Liu, Craig Brice +1
Wire-feed laser additive manufacturing (WLAM) is gaining wide interest due to its high level of automation, high deposition rates, and good quality of printed parts. In-process mon…
cond-mat.mtrl-sci2021★ 1 cited
Machine learning based in situ quality estimation by molten pool condition-quality relations modeling using experimental data
Noopur Jamnikar, Sen Liu, Craig Brice +1
The advancement of machine learning promises the ability to accelerate the adoption of new processes and property designs for metal additive manufacturing. The molten pool geometry…
cs.LG2021★ 4 cited
A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing
Rui Liu, Sen Liu, Xiaoli Zhang
To control part quality, it is critical to analyze pore generation mechanisms, laying theoretical foundation for future porosity control. Current porosity analysis models use machi…