2 papers
cs.LG2026
Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach
Mehmet Velioglu, Song Zhai, Alexander Mitsos +3
Separating liquid-liquid dispersions in gravity settlers is critical in chemical, pharmaceutical, and recycling processes. The dense-packed zone height is an important performance…
cs.LG2024
Physics-Informed Neural Networks for Dynamic Process Operations with Limited Physical Knowledge and Data
Mehmet Velioglu, Song Zhai, Sophia Rupprecht +3
In chemical engineering, process data are expensive to acquire, and complex phenomena are difficult to fully model. We explore the use of physics-informed neural networks (PINNs) f…