4 citations · 10 across the 4 of their papers we have counts for
4 papers
Unsupervised Learning of Part Similarity for Goal-Guided Accelerated Experiment Design in Metal Additive Manufacturing
Rui Liu, Sen Liu, Xiaoli Zhang
Metal additive manufacturing is gaining broad interest and increased use in the industrial and academic fields. However, the quantification and commercialization of standard parts…
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…
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…
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…